****NOW ACCEPTING APPLICATIONS****
Each year the Natural Environment Research Council (NERC) offers level 1, 2 and 3 (and 4 in the case of integrated masters) undergraduate students from any science background, the opportunity to do a paid summer placement working on a research project within the environmental sciences.
Placements are 6-10 weeks long.
For a brief introduction to the NERC REPs scheme and QUADRAT DTP please view our panopto presentation.
We are now accepting applications for summer 2021! Please make sure you are eligible before applying – see below for full details. You will also find a full list of available projects below.
Deadline: 5pm on Tuesday 1st June 2021
The Research Experience Placement (REP) are intended to encourage these students to consider a career in environmental science. During a REP, an undergraduate student joins the hosting organisation for 6-10 weeks to complete a short-term research project within the environmental sciences.
NERC has repurposed the 2021 Research Experience Placement (REP) scheme, broadening its scope to address both the quantitative skills gap (e.g. mathematics, statistics, computing, engineering) as well as demographic and diversity-related challenges in the environmental sciences. As such, we particularly welcome applications from candidates within these two groups.
A maximum of £3,200 is available per placement. This includes a salary of up to £2,700 available at the National Living Wage for each placement. A further £500 will be available for project research and training expenses if required.
The REP placement scheme is open to undergraduate students from any science discipline. Applicants must meet all of the eligibility criteria below:
• You must be a current registered student at the University of Aberdeen or Queen’s University Belfast at the time of application and for the duration of the placement. Final year undergraduate students are not eligible to apply (you cannot be graduating this year).
• You must be undertaking your first undergraduate degree (or integrated Masters).
• You must be applying for a placement in a different department (or discipline) to your undergraduate degree (see below)
- E.g. Biological Sciences students (of all degree titles: marine biology, zoology, environmental science, ecology etc) cannot apply for a project based within either of our biological sciences schools
- Discipline applies specifically to applicants from the School of Natural and Built Environment which encompasses multiple disciplines such as Geology, Geography, Engineering, Planning etc. In this case, an Engineering student could apply for a Geography project because it is a different discipline to their degree.
- You must be eligible for subsequent NERC PhD funding (details of eligibility for PhD studentships can be found here). Passport confirmation will be required for successful candidates.
We are now accepting applications for summer 2021!
Applicants should complete the below application form, as well as sending a 2-page CV (please include any placements/internships indicating whether these were paid/unpaid) and your record card / provisional transcript (as evidence of grades achieved to date) to firstname.lastname@example.org in time for the deadline.
- University of Aberdeen students can request provisional transcripts from email@example.com or you can download this from the student portal
- Queen’s University Belfast students can request provisional transcripts from the school administrator or you can download this from the student portal
Candidates may apply for a maximum of ONE placement project. Multiple applications will not be considered.
Please be advised that you cannot apply for a project within the school or discipline you currently study within e.g. a biological sciences student cannot apply to do a biological sciences REPs placement.
Please apply here: APPLICATION FORM
Deadline: 5pm on Tuesday 1st June 2021
Applications will be reviewed by the project supervisory team after the deadline. Supervisors will identify the most suitable candidate. This candidate will be invited to participate in a brief 15-20 minute interview via Microsoft Teams.
Interviews will be held by a panel of QUADRAT Board members plus an Equality & Diversity representative. The project supervisor will not be present.
You will be assessed on a variety of aspects of your application, not only your academic qualifications. Your potential to successfully deliver the project is critical, however we recognise that everyone’s circumstances are different and opportunities are not always evenly distributed. The application form allows you to identify any circumstances, past or present, that you feel might have influenced the opportunities you had/have to develop skills related to this application. Such circumstances may be directly or indirectly related to education per se. Should you choose to disclose any such information (this is entirely optional), this will allow the panel to assess, from your point of view, your skills relative to opportunities. Information of this type is confidential and will only be read by individuals who are integral to the interview and selection process.
Participation in the REPs scheme comes with a few stipulations, everything you need to know is below:
- The placement must take place for 6-10 weeks
- Placements should take place between June and September 2021
- The successful students will be required to complete temporary employment contracts at the University of Aberdeen in order for payment to be processed. These contracts restrict you to 189 hours of paid work – any work over an above this cannot be paid.
- You must keep a detailed and accurate record of all hours worked. This will have to be signed off by your project supervisor monthly.
- Your record of hours worked (dates & hours) must be submitted alongside monthly timesheets detailing your weekly hours in order for payment to be processed.
- At the end of your placement you will be required to complete an online report for NERC
- We will also ask you to write a brief testimonial for the website (see others on this page) and a blog post about your experience as part of this placement scheme.
- You will be asked to present some of your findings to our current students up on completion of the project.
You will be allocated a QUADRAT PhD student as a mentor for the duration of your summer placement. This will be a student who works in a similar or related area of research and may even be within the same research group.
In addition to this there will be opportunities to engage with our QUADRAT PhD students if you wish to learn more about their research and what it is like to undertake a PhD at either the University of Aberdeen or Queen’s University Belfast.
Project Catalogue: Summer 2021 - APPLY NOW
Title: Addressing food security through data and innovation: analysing the effectiveness of a novel fruit fly trap for small farmers in a developing country
Lead Supervisor: Dr Juliano Morimoto (firstname.lastname@example.org), University of Aberdeen, School of Biological Sciences
Second Supervisor: Dr David Fisher (email@example.com), University of Aberdeen, School of Biological Sciences
Discipline: Ecology, Entomology
Proposed working pattern: 18h /week over 10 weeks (total 180h)
This project will be delivered entirely remotely so is open to candidates at both University of Aberdeen and Queens University Belfast.
Overview: Insect pests are a major threat to global food security. For example, in Africa, huge locust swarms regularly devastate large crop plantations during their migration towards the middle east. With increasing human population and climatic changes, ensuring food security is therefore a primary global challenge recognised by major international agencies, including the UN and its sustainable development goals (e.g., SDG #2 Zero Hunger).
Problem: Insect pest outbreaks can devastate the production of small- and large-scale farmers. However, the economic costs are not confined to large outbreaks, but rather occur on a seasonal basis even when pest populations are low. A recent case occurred in Australia where only few fruit fly larvae were found in a supermarket fruit which led to a temporary collapse of food production in South Australia, with supermarkets having empty shelves and many farmers facing bankruptcy (e.g., https://www.abc.net.au/news/2021-04-04/fruit-fly-outbreaks-threatening-sa-horticultural-industry/100045806).
Developed countries such as Australia have the financial means to control pest outbreaks using sophisticated techniques (e.g., Sterile-insect-technique programs). However, this is less accessible for small farmers in developing countries. As a result, new ways to control insect pests in developing countries are urgently needed, should we wish to ensure food security in a global scale.
Objectives: This project aims to analyse the effectiveness of a novel fruit fly trap, designed to be cheaper and more efficient for local farmers in developing countries. In particular, the new trap was designed (and patented) by the industry partner in the project (Kempmann BioorganicsÂ®), and is intended to trap both female and male fruit flies (as opposed to the standard traps that attract only females; e.g., cue lure traps). The industry partner has conducted field trials to compare the effectiveness of the new trap with small-scale farmers across five field sites in India. The aim of this project is to:
1) Clean and analyse the field trial dataset provided by the industry partner, generating insights for the business as well as communicating knowledge to the academic community (through a publication)
2) Explore the data and climatic conditions, by incorporating present and future climatic data to simulate trap efficiencies under climate change scenarios
3) Provide evidence-base guidance to small-scale farmers as to whether or not the new trap can improve economic yield in the short- and long-terms, based on the field trial data.
Proposed research: This project requires the appointed REP student to:
1) Develop data analysis skills to gain insights from the dataset provided
2) Collect new climatic data, both present and future, to generate predictive models pertaining the expected performance of the new traps under climate change
3) Develop communications skills to provide insights to key stakeholders, including
a. Local small-scale farmers, through infographics and information leaflets
b. Business, through business intelligence reports
c. Academic audience, through a peer-review publication
4) Gain hands-on experience with maintenance and experimental design using fruit fly model organisms in the laboratory
Impact: This project directly addressed the SDG #2 Zero Hunger, by contributing to our understanding of food security in a developing country
Title: Optofluidic Assessment of the Thaumarchaeota Association with Pollutant Tolerance in Halichondria panicea Holobionts during Ammonia Perturbation
Lead Supervisor: Dr Cecile Gubry-Rangin (firstname.lastname@example.org), University of Aberdeen, School of Biological Sciences
Discipline: Evolutionary Microbial Ecology
Proposed working pattern: approx. 18.9 hours a week over 10 weeks (total of 189 hours)
This project is intended to be a field/laboratory-based project and is therefore only open to candidates based at a location local to Aberdeen/the University of Aberdeen.
Project description: Representing a significant portion of macrofaunal biomass and producing large quantities of biologically active secondary metabolites, Porifera are crucial to sustaining marine ecosystems by incubating and sustaining the abundant microbial communities that assist in regulating biogeochemical cycles. Despite a significant increase in studies published on Porifera-microorganism associations, relatively few genetic sequences have been conducted in order to characterise and understand their relationships and the fundamental roles of Thaumarchaeota in sponge holobionts. In the face of increasing climate change and extreme climate events further polluting global ecosystems, a shift toward consideration of sponge reefs over coral reefs in promoting marine-based environmental remediation warrants an equally comprehensive investment in understanding the symbiotic relationships between Porifera and the microbiota that drive these diverse ecosystems. This study aims to more comprehensively characterise the relationship between the Demosponge, Halichondria panicea, and a phylum of nitrifying archaea found in their microbiome, Thaumarchaeota, by assessing short-term response by the microbial community and association with pollutant tolerance during ammonia perturbation. Ammonia has been selected in place of other pollutants for this study due to its nature as both a natural and an anthropogenic pollutant capable of entering marine ecosystems through multiple means (agricultural runoff, atmospheric deposition, waste product disposal, etc.), where it can lead to eutrophication, degradation of water quality, and mass mortality of marine life currently relied upon for food, pharmaceuticals, scientific research and development, and environmental remediation. As a nitrifying archaea, Thaumarchaeota are able to acquire ammonia from the surrounding environment for metabolic consumption, making ammonia an easily accessible and applicable pollutant to be used in this study.
This project intends to combine the appointed student’s background in chemical engineering, microfluidics, and marine biology with supervisor expertise in microbiology, molecular ecology, and genetic association in evolutionary history. Research will be conducted with the assessment of relative Thaumarchaeota abundance in relation to H. panicea pollutant tolerance and mortality rate during short-term ammonia perturbation by optofluidic cell trapping and fluorescence-activated cell sorting (FACS) under impedance flow cytometry. Relative abundance results will be corroborated with specific quantitative PCR (qPCR) assays, further supporting the appointed student’s personal expertise in developing microfluidics with classically used molecular approaches.
Title: Quantitative methods for authentication of Scottish tea
Lead Supervisor: Professor David Burslem (email@example.com), University of Aberdeen, School of Biological Sciences
Second Supervisor: Dr Tassos Koidis (firstname.lastname@example.org), Queen’s University Belfast, School of Biological Sciences
Discipline: Plant and Soil Science
Proposed working pattern: 189 hours over 8 weeks
This project will be delivered entirely remotely so is open to candidates at both University of Aberdeen and Queens University Belfast.
Project description: This project will train an undergraduate student in quantitative methods for authentication of the geographic origin of Scottish grown tea. The specific learning objectives are as follows.
1. To develop understanding of sampling and experimental design of plant tissue samples and soils for geographical authentication
2. To develop knowledge and practical experience (where possible) of methods of chemical analysis of plant and soil that underpin authentication of edible products
3. To develop understanding of chemometric methods for analysing data and building predictive models derived from laboratory analyses
4. To enhance communication and networking skills based on contacts with project stakeholders
The supervisors of this project hold a library of tea samples sourced from known growers in Scotland, and a collection of more than 100 samples from all major tea growing regions of the world. This collection was amassed during a project funded by the Scottish Funding Council that connected the Tea Gardens of Scotland growers group (Tea Gardens of Scotland – growing Scottish tea plants from seed) with David Burslem for a pilot project on authentication of Scottish tea. The aim of this project was to determine whether there was evidence from multi-elemental analysis of a unique signal for Scottish tea, based on the principle that the ionomic composition of a plant tissue sample is a function of its growing environment, as determined by soil geochemistry, parent material and the local microbial communities. As part of this project, samples were collected from about 30 Scottish tea growers and a tea importer who could verify the overseas origin of about 100 separate teas. All samples were analysed for about 11 elements using ICP-MS. Preliminary analyses using principle component analyses showed clear separation in multivariate space between tea samples derived from Scotland and elsewhere, which provisionally supports the hypothesis that authentication of Scottish origin might be possible using this technique. However, uncertainties remain in the conclusion that multi-elemental composition reflects local geographical origin, and there is scope to develop the project in the context of an undergraduate research placement that would provide a training opportunity as well as extend the dataset, chemical analyses and numerical approach. The following research questions could be addressed as part of this grant (subject to circumstances).
– Is the relationship between multi-elemental composition and geographic origin consistent between years?
– What is the impact of variation in plant tissue age and type on multi-elemental composition, and to what extent does variance in these factors obscure the signal of geographic origin?
– How does multi-elemental composition in plant leaves relate to soil geochemistry and parent material?
– Do alternative methods of chemical analysis reveal similar patterns of geographic structure?
– Do alternative chemometric methods of data analysis reveal similar patterns of geographic structure?
The results from this project will be used to develop the current collaboration between the Schools of Biological Sciences at the University of Aberdeen and Queen’s University Belfast with the Tea Gardens of Scotland growers group, which has the ultimate aim of generating a certification system for Scottish tea underpinned by an evidence-based authentication method.
Title: Unmanned aerial vehicles (UAVs / drones) for the characterization of freshwater thermal habitats
Lead Supervisor: Dr Lesley Lancaster (email@example.com), University of Aberdeen, School of Biological Sciences
Proposed working pattern: Up to 189 hours over 10 weeks
This project requires some full-day fieldwork commitments during weeks 2-5 and is therefore only open to candidates based at a location local to Aberdeen/the University of Aberdeen.
Project description: Freshwater biodiversity and ecosystems are recognised as priority conservation objectives by the scientific community. Human impacts on riverine freshwater habitats are complex, involving dams for hydropower and water supply reservoirs, river channel modification for stabilization and flood control, and alterations for other uses such as canals and shipping. Such human infrastructure can both directly and indirectly impact thermal conditions of rivers. The use of temperature loggers below dams has already shown large effects on temporal (daily and seasonal) patterns of thermal variability, which may exacerbate or ameliorate effects of climate change on freshwater ecosystems. However, the spatial structure of thermal impacts downstream of dams is unknown. Discovering how dams affect thermal habitat structure is therefore an important unresolved question, given that freshwater species are in general highly reliant on the presence of thermal microrefugia to survive extreme weather events.
In this project we are exploring the use of UAVs (drones) to characterize the impacts of dams on spatial and temporal structure of thermal habitats within rivers.
Unmanned Aerial Vehicle (UAV)-based thermal images are now an affordable technology to get repeated and highly detailed thermal data to characterize water temperature landscape. However, several methodological limitations must be addressed to reach temperature accuracy needed to address biological questions (<1Â°C). The aims of the ongoing project is to (I): develop and improve appropriate thermal image calibration procedures to maximize the accuracy of the UAVs thermal images; (II) determine statistical relationships to define river bed temperature from surface temperature; (III) assess spatio-temporal thermal microhabitat variability in regulated and natural rivers using a combination of Unmanned Aerial Vehicles (UAVs) based thermal images, temperature loggers and Acoustic Doppler Current Profiler (ADCP); and (IV) Improve the understating of the implication of spatial thermal variability in freshwater community biodiversity and life stages timing, particularly for macroinvertebrates communities and known thermal need of salmonids.
AIM: Within this project framework, the student will be actively involved in (I) field data acquisition with the use direct use of ADCP and indirect use of UAVs (DJI Matrice 200 V2 equipped with FLIR XT2 thermal camera, DJI Mavic Enterprise Dual equipped with FLIR Boson 320 thermal camera); (II) macroinvertebrate sampling and classification; and (III) use of image processing software and statistical methods to aid in the development of image calibration and temperature statistical models. The student will be trained in each of these skills, providing a strong technical and analytical background in the use of field technology, image processing, and statistical analysis.
Title: Identifying and mapping hanging glaciers using satellite remote sensing with a wider scope for avalanche research
Lead Supervisor: Dr Lydia Sam (firstname.lastname@example.org), University of Aberdeen, School of Geosciences
Second Supervisor: Dr Anshuman Bhardwaj (email@example.com), University of Aberdeen, School of Geosciences
Proposed working pattern: 18.9 hrs/week for 10 weeks (189h total)
This project will be delivered entirely remotely so is open to candidates at both University of Aberdeen and Queens University Belfast.
Project description: Mountains cover nearly a quarter of Earth’s surface and are inhabited by ~1.2 billion people. Cryosphere (snow, ice, and permafrost) covers a sizable fraction of the high-mountain regions, and the meltwater supports the local ecosystems and livelihood of the resident communities. However, the complex terrain and rapidly changing global climate are making the mountains increasingly prone to natural hazards such as avalanches, flash floods, landslides, glacier outbursts, and glacial lake outburst floods (GLOFs). The rising frequency of such disasters, coupled with increasing tourism and resource-exploitation-driven population load on mountain regions, is further escalating the risk. Ice avalanche is one such disaster which can have widespread hazardous implications for the local population. Such ice avalanches are often generated by breaking or sliding hanging glaciers in high-mountains. Hanging glacier is a type of mountain glacier that originates high on the wall of a glacier valley and descends only part of the way to the surface of the main glacier. Avalanching and icefalls are the mechanisms for ice and snow transfer to the valley floor below. Therefore, before starting a regional-scale ice avalanche research, it is important to identify, map, and study the hanging glaciers which are prone to ice avalanching.
In the present project, we aim to use high-resolution satellite images to identify and map hanging glaciers in an avalanche-prone region of the Himalaya. This effort will be part of a bigger effort later on, where the identified hanging glaciers will further be assessed for their hazard potential. The expected data proposed to be compiled through this project can be a great value addition in terms of quantitative and qualitative assessment of the spread of hanging glaciers in the region. This will also be first such regional inventory exclusively documenting the hanging glaciers.
Thus, the present project will have the following research objectives:
1. To use high-resolution satellite images to identify and map hanging glaciers in a selected region of the Himalaya.
2. To compile the generated data in an inventory format.
3. To analyse salient distribution statistics of the hanging glaciers.
This project will get benefited from the quantitative skills of the candidate of a statistical, computing or mathematics background. In return the candidate will be trained on downloading, processing, and analysing remote sensing datasets, and subsequently performing mapping and geospatial analysis in Geographical Information System (GIS) environment. Thus, the candidate will be able to understand the frequency and spread of the hanging glaciers across a high-mountain valley and will further be able to analyse the future challenges in modelling ice avalanche hazards in the region. This project will offer the candidate enough opportunity to apply his/her skills and to take initiative in uniquely analysing Earth observation data for humanitarian purposes.
Title: Researching a Demonstration Project as the Basis to Develop and Implement an Innovative and Sustainable Approach to Mitigating the Loss of Golf Courses from Coastal Erosion
Lead Supervisor: Dr David R Green (firstname.lastname@example.org), University of Aberdeen, School of Geosciences
Second Supervisor: Ray Lawrenson (email@example.com), Siskin Group
Proposed working pattern: approx. 20hrs a week for 9 weeks
This project requires some practical and field work and is therefore only open to candidates based at a location local to Aberdeen/the University of Aberdeen.
Project description: Coastlines are subject to dynamic change through wave/wind action resulting in significant loss/gain of land through erosion/accretion. A focus on developing new low-cost environmentally tolerable/sustainable solutions will therefore be important. Traditionally, durable defences against erosion are based on hard-engineering. Siskin Asset Management Ltd., however, have developed a new concept based on well-recognised soft-engineering techniques. These have been enhanced to improve durability and resilience in common coastal conditions. This delivers mitigation of erosion at a lower up-front and reduced lifecycle costs whilst being deployable using community level resources. Based on soft-engineering methods the concept therefore has a low environmental footprint.
The method proposed will use a by-product of forestry operations called ‘brash’, similar to ‘Christmas tree’ waste. This natural product is baled before being arranged in a defined geometry and anchored in the back-beach-area of soft coastlines. This structure acts to capture mobile sediment and to promote re-vegetation of the existing coast, the effect being to enhance the resilience of the coastline against wave/wind attack.
The soft-engineering solution is low-cost, easily managed and replaced, and can be scaled up or down to meet the needs of the coastal erosion challenge faced by many coastlines where erosion is rapidly placing assets at risk.
This is an applied research project with elements of modelling, GIS, geo-statistics, remote sensing and engineering. An interest in drones and their application is desirable. Practical support will be provided by the University (AICSM, GIS, and UCEMM), DroneLite (drone company), Siskin Asset Management Ltd., R&A, and relevant Local Authorities..
The 6-10 week project will be built around researching the contextual and background knowledge that exists relating to the proposed coastal management concept, the placement of the structure, and its monitoring and modelling as a means to demonstrate the protection with the aim of scoping out some field trials which could then form the basis for future research work which supports the Siskin concept.
This will involve the following:
1. Familiarisation with the Siskin concept, its construction and implementation
2. Familiarisation with statutory planning processes
3. Familiarisation with the scientific research literature on e.g. coastal geomorphology, coastal management and protection, coastal processes and coastal engineering
4. Familiarisation with and participation in drone surveys with some field training on the operational aspects of accurate drone surveying
5. Familiarisation with soft-copy photogrammetry software to generate deliverables e.g. .ortho-photos, 3D terrain and surface models
6. Familiarisation with environmental impact assessment (EIA)
7. Understand what natural vegetation might grow best in the environment created by the installation of the Siskin system
8. Establish a collaborative arrangement with coastal management research team of Professor Andrew Cooper and Professor Derek Jackson at the University of Ulster (Coleraine) to link into some of their research and insights for coastal study sites in Northern Ireland
This will necessarily involve collaborative research meetings and some education and training to provide the necessary support framework and guidance to carry out the proposed work.
Title: Understanding the distribution of thermokarst lakes across the Himalaya
Lead Supervisor: Dr Anshuman Bhardwaj (firstname.lastname@example.org), University of Aberdeen, School of Geosciences
Second Supervisor: Dr Lydia Sam (email@example.com), University of Aberdeen, School of Geosciences
Proposed working pattern: 18.9 hrs/week for 10 weeks (189h total)
Project description: Thermokarst refers to landscape processes associated with or promoted by the thawing permafrost or melting ground ice in glaciated regions. Therefore, the thermokarst terrains are usually characterised by irregular surfaces such as mounds or hummocks and localised subsidence/depressions often filled with water, forming ponds/lakes. These thermokarst lakes continue to grow with rising temperatures and a positive feedback mechanism where the water absorbs more solar radiations further degrading the underlying permafrost. Therefore, the presence and expansion of thermokarst lakes is considered as a reliable marker of climate change/warming and it often corresponds to unstable permafrost regimes. Moreover, thermokarst lakes and ponds are also one of the geomorphological indicators for rock glacier and mountain permafrost. This further highlights the significance of thermokarst lakes for short- and intermediate-term impact on local hydrology. Thermokarst lakes are the predominant type in Arctic permafrost regions and are mostly characterised by shallow water depth and small area, depending on the initial ground-ice distribution and the sediment supply. However, they are also present in the high-mountain environments such as the Himalaya, mainly in the periglacial regions with gentler valley slopes. Although hundreds of thermokarst lakes are spread across the Himalayan mountains, the exact number, distribution, and areal coverage of these lakes is not known. Despite the importance, detailed studies on thermokarst lakes and permafrost thawing and its impacts of high mountain landscapes and ecosystems remain elusive for the Himalayan region. Thus, the proposed study will be a starting point for understanding the distribution of thermokarst lakes across the Himalayan terrain.
In this project, we aim to use high-resolution satellite images to identify and map thermokarst lakes within a defined region of Himalaya. The expected data proposed to be compiled through this project will be unique for the Himalayan region and can be a great value addition in terms of quantitative and qualitative assessment of the spread and status of permafrost in the region.
Thus, the present project will have the following research objectives:
1. To use high-resolution satellite images and identify and map thermokarst lakes across the Himalayan region.
2. To compile the generated data in an inventory format.
3. To analyse salient distribution statistics of the thermokarst lakes.
This project will get benefited from the quantitative skills of the candidate of a statistical, computing or mathematics background. In return the candidate will be trained on downloading, processing, and analysing remote sensing datasets, and subsequently performing mapping and geospatial analysis in Geographical Information System (GIS) environment. Thus, the candidate will be able to understand the frequency and spread of the thermokarst lakes across the Himalayan region and will further be able to analyse the impacts of climate change on the water resources in the Third Pole. This project will offer the candidate enough opportunity to apply his/her skills and to take initiative in uniquely analysing Earth observation data for environmental research.
Title: ARCZero (Accelerating Ruminant Carbon Zero): Accelerating the pathway to carbon zero farming by measuring and managing carbon flows at the individual farm level and empowering farmers to make positive change
Lead Supervisor: Dr Paul Williams (firstname.lastname@example.org), Queen’s University Belfast, School of Biological Sciences
Second Supervisor: Professor Nigel Scollan (email@example.com), Queen’s University Belfast, School of Biological Sciences
Discipline: Biology, Soil Science, Biogeochemistry
Proposed working pattern: 18.9 hrs/week for 10 weeks (189h total)
This project requires some field work and is therefore only open to candidates based at a location local to Belfast/Queen’s University Belfast.
Overarching Aim: By assessing future management practices and identifying the most impactful behaviours the project intends to inform how farms across Northern Ireland could accelerate the move towards net carbon zero farming.
Objective 1: Actual individual net farm GHG footprints in NI are currently unknown as most current methodologies calculate gross GHG footprints for farm enterprises & do not accurately assess on-farm carbon stocks and their potential for annual carbon sequestration. Accelerating Ruminant Carbon Zero (ARCZero), a European Innovation Partnership project, seeks to measure and manage carbon flows at the individual farm level to empower farmers to make positive change towards carbon zero agriculture. This placement is a unique opportunity to partake in the initial field recognisance and data collection from this Northern Irish initiative to establish whole farm carbon stocks, annual emissions and soil fertility baselines. Working with the ARCZero ambassador farm network, a collective of 7 commercial farms, this project maps/overlays physiochemical soil sustainability indicators within a framework of benchmarked current practices encompassing dairy, beef and lamb farming types, geolocated across the dominant agri-scapes of NI, which includes native Irish woodland and hedgerow habitats.
Objective 2: Underpinning soil carbon stock predictions/estimates are sector standard calculations based on ex situ bulk density measurements. Typical soils in NI contain far greater concentrations of SOC than their GB counterparts. It is hypothesized here that disparities between in situ field density and laboratory determined equivalents result in significant biases in final LCA modelling. This will also be investigated in this project in collaboration with Cawood scientific Ltd.
Objective 3: Simple measures of appropriate levels of soil organic matter are needed for soil evaluation, management and monitoring, based on readily measurable soil properties. An index of soil organic matter based on the soil organic carbon (SOC) to clay ratio, defined by thresholds of SOC/clay ratio has been proposed based on a study on English and Welsh soils (Prout et al. 2020). The index should work for NI soils, but this posit needs testing.
Teaching proposed. During the project there will be opportunities to learn about all the component entities of the AgReCalc LCA. The candidate will receive training in field work skills by partnering with a team of professional/accredited sampling agents. They will learn site assessment skills, identification of on farm activities and land-use scoring. There will also be opportunities to learn about LiDAR survey and analysis to identify above ground carbon storage and routes of overland flow.
Chemical analysis of the sampled soils will be undertaken by Cawood scientific Ltd. However, training in quality control protocols, nutrient soil testing and data processing will be provided.
Communication skills such as presentations will be fostered via regular meetings and updates to/with the ARCZero management board and QUB students. The project will also foster additional engagement opportunities with partner organisations such as AgriSearch, Devenish, AFBI and Birnie Consultancy.
Prout, J. M.; Shepherd, K. D.; McGrath, S. P.; Kirk, G. J. D.; Haefele, S. M. What Is a Good Level of Soil Organic Matter? An Index Based on Organic Carbon to Clay Ratio. Eur. J. Soil Sci. 2020.
Title: Behaviour and growth in fallow deer fawns
Lead Supervisor: Dr Isabella Capellini (I.Capellini@qub.ac.uk), Queen’s University Belfast, School of Biological Sciences
Second Supervisor: Dr Domhnall Jennings (D.Jennings@qub.ac.uk), Queen’s University Belfast, School of Biological Sciences
Discipline: Ecology / Animal Behaviour / Behavioural Ecology
Proposed working pattern: Approx. 3 days/week over field data collection (video recording) of fawn behaviour (from July to mid-August) followed by data extraction and analysis.
This project requires field work in Dublin 2-3 days a week for about 6 weeks to collect data and is therefore only open to candidates based at a location local to Dublin/Belfast/Queen’s University Belfast.
Project description: Physically larger juveniles typically have better chances of surviving their first year of life, reach maturity sooner and achieve greater reproductive success later in life. Thus, how quickly individuals invest in growth early in life is a key life history trait, which also varies substantially between individuals. However, growth patterns have been predominantly studied in farmed and zoo animals showing that, in mammals, growth rates are higher with greater suckling frequency, duration of suckling bouts, and more energy rich milk, and that males grow faster and longer than females in sexually dimorphic species. However, we know remarkably little about how individuals grow in the wild and how their own behaviour contributes to their growth trajectory. Specifically, in the wild individuals need to balance energetic investment towards somatic growth against investment in energetically expensive behaviours (e.g. play) that determines current and future survival (e.g. escaping predators). Thus, juveniles need to trade off energy acquisition (suckling) and energy saving behaviours (sleep, rest) against locomotory and social behaviour. Captive individuals have easy access to resources and no predators to escape from, therefore studies in captivity cannot fully address questions on how and why growth varies between individuals in the wild.
This project uses fallow deer fawns at Phoenix Park (Dublin) as a model. Fawns are individually identifiable through unique coloured and numbered ear-tags. Nearly all fawns are captured within days after birth, aged, weighted, ear-tagged, and physiological and behavioural measures of their response to handling are taken. Individuals in this population are easy to observe as they predominantly spend their time in the open with the doe herd during the day and are habituated to people. Fawns in this population also face predation by foxes and occasionally dogs. Furthermore, this spring 20 fawns will be collared for an independent project and will represent the focal sample for the study proposed for this research placement.
The objectives of this project are:
1. To estimate growth rates fortnightly indirectly using established, non-invasive photogrammetry methods for wildlife (e.g. Adams et al 2020 J Zool).
2. To record fawn behaviour on camera and derive individual time budget over the summer focusing on key behaviours (frequency and duration of bouts of suckling, play, rest awake, sleep, walking and running).
3. To assess how growth rates vary in relation to individual investment in different behaviours using appropriate statistical tests.
The student will learn how to:
1. Use photogrammetry to measure fawn growth.
2. Collect behavioural data in the field using appropriate protocols and derive activity budgets.
3. Run appropriate statistical analyses to answer the questions of the project.
The student will be part of our group of students and staff investigating different questions on fawns and mothers’ behaviour.
Title: Earthworms and soil engineering under climate change
Lead Supervisor: Professor Eric Morgan (firstname.lastname@example.org), Queen’s University Belfast, School of Biological Sciences
Proposed working pattern: Approx. 189 hours over 10 weeks
This project requires fieldwork local to Belfast and is therefore only open to candidates based at a location local to Belfast/Queen’s University Belfast.
Project description: Earthworms are crucially important to nutrient cycling, soil structure and carbon storage on livestock pastures, and are involved in less understood processes including parasite transmission. Despite this there is little information on how environmental change affects earthworm abundance and activity, in terms of climate change and also local environmental conditions such as plant composition.
This project would investigate earthworm communities across different agricultural pastures, and trial mesocosm-based approaches to assess the impact of environmental change on earthworm-driven dung incorporation into soil.
The successful student will be paired with a PhD student, within a dynamic research team working on integrated parasite control on livestock farms in Northern Ireland. Visits to participating farms will be arranged for field work. Previous results identified that pasture type may change earthworm communities; however, within pasture differences are yet to be examined. The student could use vermifuge methods to extract earthworms and identify how abundance or diversity changes in different environments. Mesocosm-based approaches could be subsequently adopted to investigate impacts of different earthworm communities on dung mass over time. This would involve setting up mesocosms in which earthworm communities are isolated and either denuded or augmented, and tracking dung incorporation over time in relation to weather and environmental factors. This will indicate how changes in earthworm communities could have knock-on effects for agricultural processes, such as dung movement, nutrient cycling and organic matter incorporation to the soil.
This basic work will provide skills and experience in earthworm extraction and identification from field sites, and mesocosm design and implementation, and generate a data set on which to practise quantitative statistical analysis, with guidance. The student could additionally model how changes in climate may impact dung degradation, adapting existing model frameworks and software, and gaining skills in ecological modelling and programming.
The work follows a planned risk profile, whereby the above is highly likely to generate good experience and data, a sub-set of which will be used to answer the placement student’s own research questions. A second component will be entirely led by the student with support from the wider group. This will investigate the potential to modify mesocosm design to incorporate a local climate warming element. Thus, a variety of open-topped climate chambers have been developed for ecological studies, generally consisting of sloping perspex walls and achieving local warming of the soil surface while allowing rainfall. The student would combine this approach with the earthworm mesocosms, which wall off soil to limit earthworm immigration and emigration, and measure effects of local soil warming on earthworm activity. This would run in parallel to the main study using access to pastures to evaluate prototypes. Depending on initial test steps and student training aims, a pilot study could be conducted to evaluate effects of soil warming on pasture microclimate, plant growth, dung burial, and/or development of parasite larvae on herbage (from naturally infected dung). Instruments available to support this work include data loggers to record temperature at different depths, and drones with spectral cameras to map surface structure and microclimate.
Title: Discovery of interactions between river properties and bridges within built infrastructure
Lead Supervisor: Dr Myra Lydon (email@example.com), Queen’s University Belfast, School of Natural & Built Environment
Second Supervisor: Professor Jenny McKinley (firstname.lastname@example.org), Queen’s University Belfast, School of Natural & Built Environment
Discipline: Civil Engineering
Proposed working pattern: 189 hours over 9 weeks
This project required field/lab work and facilities access local to Belfast and is therefore only open to candidates based at a location local to Belfast/Queen’s University Belfast.
Overview: The management of our built and natural environments happen largely in isolation of each other, bridges allow our transport networks to span the complexities of our natural landscape and over of 80% of road bridges in Northern Ireland carry a road over a river. Yet little consideration is given to how the natural properties of that river impact the condition of the bridge which crosses it. In order to make this connection for the first time our bridges must be physically linked to the rivers they cross.
Objectives: The research will aim to create this link through geographical information systems (GIS). This will require the student to capture field data in terms of bridge location and geometry and also validate existing location data and detailed in data collection section of this form.
Learning outcomes/teaching: The student will learn about the basic functional properties of bridges and gain field experience in data collection and input for GIS to create a spatial link between bridges and rivers. The student will then undertake some exploratory research in spatial assessment of the data supported by the Department for Infrastructure (DfI) and QUB. DfI currently collect a range of spatial data across infrastructure in Northern Ireland (NI). The student will have the opportunity to engage with the department and learn about the various data collected. The student will be supported in learning advanced analysis in GIS linked to the Centre for GIs and Geomatics, QUB and will be given access to Dr Lydon’s DataCamp membership class to avail of a full suite of online guided training in statistical analysis.
Title: Investigating the relationship between climatological variables and the timing of lake and river ice phenology
Lead Supervisor: Dr Andrew Newton (email@example.com), Queen’s University Belfast, School of Natural & Built Environment
Second Supervisor: Dr Donal Mullan (firstname.lastname@example.org), Queen’s University Belfast, School of Natural & Built Environment
Proposed working pattern: 189 hours over 10 weeks
Project description: Lake ice phenology is governed by a number of factors, mainly the geographical setting (which impacts heat exchange, wind, precipitation, latitude, and altitude) and the site-specific morphometry and heat storage capacity of the water body. Analysis of the relationships with ice phenology is much easier for the former than it is for the latter, and given the potential application of remotely-sensed or modelled datasets it can open up the potential for studies at a hemispheric scale. Owing to the distribution of landmasses, the vast majority of lakes and rivers that seasonally freeze are located around the high latitudes and altitudes of the Northern Hemisphere. Consequently, much of the research that has been carried out has focused on these sites, and has tended to explore changes in breakup/freezeup dates, ice season length changes, and ice thickness variations. A major problem going forward is that, whilst there is a substantial knowledge basis, an assessment of changes in broader ice phenology is complicated by, among several factors, the tendency to consider only local case studies. This makes it harder to upscale results to the hemispheric scale and envisage what the large-scale consequences of the changes might be. During this placement the student will be introduced to topics related to climate change and in particular the state of knowledge on lake and river ice. The student will have access to a number of raw datasets that capture climatological and ice phenology data captured across the Northern Hemisphere. There are millions of observations in these datasets that have rarely been brought together in such a way. The student will ideally be mathematically inclined and will have experience with coding independently. They will compile coded projects that source, organise, and interrogate the data to understand the underlying drivers of ice phenology change for ~1500 Northern Hemisphere sites. The main outcome will be to develop site-specific matrices that help to explain what climatological factors have driven the changes observed in movements of ice breakup and freezeup dates. These site-specific details can then be investigated at the hemispheric scale to gain a deeper understanding of ice phenology variation. The expectation is that the statistical analysis will provide a unique insight into environmental change over the last ~200 years. The results will be of significant benefit to the community and it is expected that the student will also be able to play a part in writing up these results (if they wish) for publication as a co-author. The student will have access to a supervisory team with expertise on ice phenology and climate change analysis. It is expected that this project will provide a means for two-way communication and learning from student to supervisors. When the project is complete the student will have developed new processed datasets and also gained an appreciation for a key area in environmental change that is poorly understood. They will benefit from new insights into how their underlying expertise can be applied to solving environmental problems that are not traditionally associated with their discipline.
Title: Investigation of inter-annual, seasonal and diurnal variability in pollen rain
Lead Supervisor: Dr Gill Plunkett (email@example.com), Queen’s University Belfast, School of Natural & Built Environment
Second Supervisor: Dr Lisa Coyle McClung (firstname.lastname@example.org), Queen’s University Belfast, School of Natural & Built Environment
Discipline: Archaeology & Palaeoecology
Proposed working pattern: 180 hour over six weeks (approx. 30 hrs per week)
This project required fieldwork local to Belfast and is therefore only open to candidates based at a location local to Belfast/Queen’s University Belfast.
This project required field/lab work local to Belfast. Please only apply if you are based at a location local to Belfast/Queen’s University Belfast.
Project description: The aim of this project is to determine the relationship of pollen production and meteoreological variables, especially temperature, and to explore multi-year seasonal and diurnal changes in pollen productivity. The project will entail the collation and analysis of Belfast pollen rain counts to examine temporal fluctuations in pollen production in relation to meteorological data.
Archive pollen count data are readily available at QUB, and include counts that permit separation of pollen rain by time and date during the pollen rain season (March to September). At the outset of the placement, the student will be trained in the use of the pollen trap at QUB and identification of pollen rain to provide a firm foundation for interrogating the data (including an understanding of its limitations), and short lectures and set reading will ensure that the student is familiarised with the principals of pollen production and dispersal, and its allergenic properties. Simultaneously, training will be given in data collation (spreadsheets) and analysis (time-series analysis and statistical correlation). The student will be asked to consider trends and patterns in the data, and to investigate the ecological background of critical taxa to gain a deeper understanding of the significance of the data. Training will also be provided in the preparation of a formal report of the results.
The project will be co-supervised by Dr Lisa Coyle McClung who leads the Met Office pollen monitoring at QUB. Mentoring will be provided by a Cohort 2 QUADRAT student at QUB.
Title: Testing Bayesian 210Pb age-model on real-world data
Lead Supervisor: Dr Maarten Blaauw (email@example.com), Queen’s University Belfast, School of Natural & Built Environment
Discipline: Archaeology & Palaeoecology
Proposed working pattern: approx. 16 hours per week over 8 weeks (128hrs total)
Project description: In this project, a new numerical age-model approach will be tested on a wide range of existing Pb-210 datasets. Pb-210 is a radioactive isotope with a half-life of 22.3 years. Measurement series of Pb-210 in cores from bogs and lakes enable such cores to be placed on the calendar scale. Since such deposits form natural archives of recent environmental change, 210Pb dating has become a key tool to inform us about recent environmental changes including pollution, erosion, and man-made climate change.
Current numerical techniques to interpret Pb-210 data were developed in the 1970s and are known to be limited in their abilities to provide reliable time-series. They often only extend back to 100 years, cannot be combined with other dating information, have problems dealing with missing data, are not very flexible, and the uncertainty estimates are overly optimistic.
We have recently published ‘Plum’, a Bayesian alternative which should enable the production of much more robust Pb-210 time-series. Simulations and tests on a limited range of existing datasets indicate that our approach can extend the time-series several decades further back in time, can deal with outliers and missing data, and can include other dating information. However, we still don’t know how well the approach works on a wider range of Pb-210 datasets.
In this summer project, the student will collaborate with a local supervisor (who was involved in the initial development of Plum and is developing and maintaining its R package) and with collaborators in a range of well-known Pb-210 laboratories around the world, from Exeter in the UK to Minnesota (US) and Mazatlán (Mexico). Through testing Plum on many existing datasets, including challenging ones, we will be able to get to know better the possibilities and limitations of Plum, and moreover the tests will be used to list possible improvements to the software.
The student will be able to participate in testing and developing this promising new technique, and if interested and capable could also participate in programming to implement improvement and test how they enhance the chronologies. The student will be taught key concepts of age-modelling and its importance for reconstructing environmental change over the past century.
“I’m an MSci Mathematics student at Queen’s University, Belfast, entering into my third year of study. This placement was an invaluable opportunity for me to gain experience in research by working alongside an expert in the field in my project titled “Climate change and the future viability of Europe’s longest Ice Road”.
During this project, I was able to work with large sets of data and perform various forms of regression analysis to model how the thickness of the ice roads in seven different locations vary with the temperature. I then compared a number of different models which predicted how the temperature patterns will change over the next 100 years and corrected them for bias. With the models and the future temperature data, I was able to produce predicted values for the thickness of the ice roads in the future for three different climate change scenarios – a temperature increase of 1.5°C, 2°C and 4°C globally.
I was finding it difficult to decide which area of maths I wanted to specialise in, but my work in this project opened my eyes to how much I enjoyed performing statistical analysis, and how rewarding it feels to come to the end of a research project and see what your work has achieved. I have been inspired to change my degree pathway to Mathematics with Statistics and Operational Research, and once I have finished my masters, I now hope to go on to complete a PhD in statistics and enter into the world of academia and research.”
Read more about Emily’s project on the QUADRAT blog.
“Hi! I am a Mathematics & Computing Science student at the University of Aberdeen. I am finishing my BSc this academic year, and my plan is to jump straight into a masters’ degree in Artificial Intelligence after that. I am already between two departments with this degree, but I was super excited to collaborate with researchers from School of Biological Sciences, further strengthening the bond between departments. My project in the NERC-QUADRAT scheme was called: “Implementing a Machine Learning Approach for the understanding of social learning in honeybee foragers”, which is quite a mouthful.
During the 10 weeks of this project, I worked closely with the researchers to identify the genes that play a key role in the waggle dance. We have used several machine learning algorithms, such as Support Vector Machines, in the programming language R. The pragmatic mindset of a programmer was a major benefit here as it allowed me to see the dataset unbiased. At the end of the project we have successfully compiled a list of possible genes that play a great role during the waggle dance of honeybee foragers. To summarise, this has easily been the most interesting project I have contributed to in my career so far.”
Read more about Marcell’s project on the QUADRAT blog.
“I am an Electrical and Electronics Engineering Student at the University of Aberdeen. A big reason why I decided to study engineering was the wide range of applications, so I was excited when I heard about the opportunity to put my skills to practice in the field of climate change research. I worked on a project called: “Modelling historical ice phenology data and implications for future environmental change”.
During my 10-week placement I processed numerous raw datasets from over 1500 sites capturing environmental data over ~500 years using Python. My background in programming allowed me to use algorithms to automate the statistical analysis, observing key trends in the data to gain a better insight into the changes in ice seasons of lakes and rivers in the Northern Hemisphere. I found it highly motivating, knowing that my work was going to contribute to future research. The placement not only strengthened my confidence in my own capabilities but also encouraged me in my decision to pursue a Data Science masters.”
“Hi, my name is Scott Angus and I am a Physics student at the University of Aberdeen and have just started my third year of studying. My summer research project was titled “Geostatistical analysis of spatiotemporal trends of COVID-19 spread in UK”. I saw this placement advertised in an email from the NCS School office and it looked like something that would really interest me as it involved a very current and world-changing topic as well providing an opportunity to work with a new approach to statistical analysis using Geospatial data.
During this project I worked with my two supervisors to gather the daily data regarding the COVID-19 pandemic and compile this into various datasets before working with this in both ArcGIS and R Studio. We analysed the spatiotemporal trends in the spread of the disease and created statistical models to evaluate the effectiveness of various non-pharmaceutical interventions put in place by the Government.
I found it really exciting and rewarding to work on such a topical and rapidly developing area of research, the results of which could help combat future pandemics more effectively and save lives. It also inspired me to do further research in this area for my final year project and beyond.”
Read more about Scott’s project on the QUADRAT blog.
“My name is Milena Zagulak and I’m a 4th-year Mechanical Engineering student at the University of Aberdeen and I was fortunate enough to work on a very exciting project this summer called “Assessing the long-term impact of climatic variables on coastal changes in Scotland using geospatial tools”. Before starting the project I already had some background in working within the coastal science environment, however, I wanted to experience the real, cutting-edge research.
During my placement, I composed a library of Landsat images of Scotland between 1970s-2010s, which were used to map out the changes in the Scottish coast in that period and quantify them using ArcGIS Software. Later on, I performed statistical analysis of the meteorological data from various stations around Scotland and how climatic variables such as precipitation and temperature might be linked to the changes within the coast.
I found it very exciting to contribute to such an important project as such a detailed assessment of the whole Scottish Coast has not been done before. The placement helped me to understand what real research entails and encouraged me to further pursue environmental science, hopefully in a form of a PhD or research work.”
All science and quantitative disciplines are eligible however you must apply to a project based in a different school/department to that of your degree. How does this work in practice?
- For example, Biological Sciences students (of any subject are: marine biology, zoology, environmental science, ecology etc) cannot apply for a project based within either of our biological sciences schools, even outwith their immediate degree title e.g. a marine biology student is NOT eligible to apply for an ecology based project. The disciplines are too similar.
- The School of Natural and Built Environment (QUB) encompasses multiple disciplines such as Geology, Geography, Engineering, Planning etc. In this case, you must apply for a project in a different discipline. For example, an Engineering student could apply for a Geography project because it is a different discipline to their degree, even though it is within the same school.
Please email firstname.lastname@example.org if you have any questions.
All science disciplines are eligible however NERC are particularly interested in candidates with quantitative skills developed outside of the usual NERC subjects. These disciplines include but are not limited to: mathematics, statistics, computing, engineering, physics and chemistry.
Please apply for a maximum of one project. Multiple applications will not be considered.
Yes, you must currently be studying for a non-NERC science undergraduate degree at either the University of Aberdeen or at Queen’s University Belfast. You must be a registered student at the time of the placement taking place and therefore final year undergraduates, recent graduates and alumni are not eligible to apply.
A salary of up to £2,700 is available at the National Living Wage. The successful candidates will be set up as employees and paid a salary at the university’s current living wage of £9.30. The salary will be paid monthly in arrears following submission of a monthly timesheet. A further £500 will be available for project research and training expenses, the costs of which must be itemised and justified in the final report.
Table 1 UK national minimum wage across age-groups (as of April 2021):
|Length of REP||18 – 20 years old||21 – 22 years old||23+|
This table is based on 2021 National minimum wage; NERC will provide £3200 per REP including £500 for research costs
Placements will be on a part-time basis, likely 2-3 days per week (max. 189 working hours over the duration of the project). This equates to approximately 18 hours (c. 2.5 days) per week for 10 weeks.
You will need to agree a suitable working pattern with the project supervisor – hours can vary from week to week but must not exceed 189 hours in total. REPs placements must be 6-10 weeks long, therefore you cannot complete all 189 hours in fewer than 6 weeks.
You will need to keep an accurate record of hours worked, week by week on the project. Monthly timesheets will be required.
No, unfortunately final year students are not eligible to apply because they will no longer be a registered student with the institution at the time the placement takes place.
Unfortunately not. If you are completing your honours project and will graduate this year then you are not eligible to apply.
No, the REPs placement is an extra-curricular activity and does not contribute towards your degree but is a valuable experience and opportunity to develop new skills.
In this case (amalgamated schools such as SNBE at QUB), students within the non-NERC disciplines are eligible to apply both to the projects within their school/department (but out with their own discipline) as well as to projects in other schools. For example, a civil engineering student based in SNBE could apply for a project within the discipline of Geography, but a Geography student could not. If you are at all unsure please email email@example.com for clarification.
No prior knowledge or education in the environmental sciences is required. Projects do not assume knowledge in these areas but instead put value on the quantitative skills you can bring to the environmental sciences. Training will be provided and funded where necessary.
This depends on the project and the work that is required. Some projects require a candidate with a specific background (such as a computer science student) or a specific skill set (such as coding), but others are more general. You are asked to demonstrate how you meet the needs of the project in the application form. Supervisors will select candidates with the most appropriate skills for the project.
Some projects will require you to already have specific skill sets such as coding (specified in project description), however additional training will be provided in the areas required for you to complete the project. Training will vary from project to project – some details are given in the project overview, but supervisors can provide more information if required.
It is expected that applicants will have the capacity and computing infrastructure (internet connection and laptop / desktop computer) to work from home, however some supervisors make specific mention of the availability of a laptop (please see project descriptions). It may also be possible to borrow a laptop from the central university. Please speak to the supervisor in the first instance. Supervisors will provide access to any specialist software.
You are not required to contact the supervisor before applying, but it may be beneficial to do so if you have questions about the project content or skills required.
After the deadline has passed, supervisors will assess the applications they have received and identify the most suitable candidate. One candidate for each project will be asked to attend a brief interview (10-15 minutes) via Microsoft Teams. Once the interviews have been completed, the top 5 candidates will be awarded the project and funding. We will notify you of the outcome of your application as quickly as possible.
Students should submit a record card (University of Aberdeen) or a provisional transcript (Queen’s). University of Aberdeen students can download this from their student portal or contact firstname.lastname@example.org for this.
There will be some paperwork to set up your temporary contract at the University of Aberdeen. This is necessary in order for us to pay you on a monthly basis.
It is a NERC requirement that both the candidate and the supervisor complete a brief final report form upon completion of the placement. This online form will be circulated towards the end of the placement. We also ask that you write a brief testimonial for the QUADRAT website and a short blog post about your placement experience. These resources are useful for future applicants.
A passport check will be undertaken to confirm successful candidates’ eligibility to work in the UK. This process will vary depending on which institution you are registered at, and which project you will be undertaking (whether it is at Aberdeen University or Queen’s).
We especially welcome applications from underrepresented demographic groups. ‘Underrepresented demographic groups’ is a very broad and inclusive term which may include but is not limited to the following:
– candidates with a disability
– candidates from ethnic minorities
– first generation university attendees
– candidates from low income / widening participation backgrounds
– candidate who identify as LGBTQ+
– candidates with caring responsibilities
– candidates who, for whatever reason, have had fewer development opportunities
We understand that everyone’s circumstances are different and this cannot always be easily defined. The application form has space for you to write an optional statement for you to include any other information you would like us to consider alongside your application. The above give an indication but is not an exhaustive list.
Yes, you are still eligible to apply but preference will be given to candidates from a quantitative discipline or an underrepresented demographic group.