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.

DEADLINE: NOW CLOSED

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.

In 2021 NERC repurposed the 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.

FUNDING
A maximum of £3,312 is available per placement. This includes a salary of up to £2,812 available at the National Living Wage for each placement. A further £500 will be available for project research and training expenses if required.

ELIGIBILITY

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.

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 sbsinternships@abdn.ac.uk in time for the deadline.

  • University of Aberdeen students can request provisional transcripts from studentrecords@abdn.ac.uk 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: NOW CLOSED

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 2022
  • 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 2022

Title: Timing the introduction of fallow deer fawns to the social group: the role of fawn sex, maternal age and experience

Lead Supervisor: Domhnall Jennings (d.jennings@qub.ac.uk), Queen’s University Belfast, School of Biological Sciences

Second Supervisor: Greta Bocedi (greta.bocedi@abdn.ac.uk), University of Aberdeen, School of Biological Sciences

Discipline: Animal Behaviour

Proposed start date: 27/06/2022

Proposed working pattern: 31h /week over 6 weeks (total 186h)

The field component of the study will be based in Phoenix Park, Dublin. Following completion of this phase of the project, the student will work in the School of Biological Sciences at Queen’s University Belfast. Please consider this when applying since the budget for research costs, including travel, is limited.

Project description:

Project Outline: The fallow deer is a hider species; at about the time of birth mothers (does) leave their social group and move to a secluded area where they give birth in seclusion. Following the birth, the doe leaves her fawn hidden in undergrowth, and returns periodically to nurse and bond with her offspring. Once the fawn gains strength and mobility, the doe introduces it gradually to the wider social group; nevertheless, the timing of this introduction is highly variable with some fawns rapidly socialised, whereas other are not observed in the herd for some months. Our understanding of why there is such variability in the socialisation process is poor; however, it is possible that the age of the mother, and her experience successfully raising offspring may play a role in this timing. Specifically, that less experienced mothers may use an early socialisation strategy with time of socialisation correlating positively with age. Alternatively, it may be the level of investment required by the offspring that is the key factor; thus, because male fawns usually require higher levels of maternal investment, we might expect to see male fawns introduced to the herd at younger ages than females. The purpose of this project is study this question.

Objectives: There are two project objectives: (1) investigate whether maternal age and experience plays a role in the timing of fawn introduction to the social group, and (2) to determine whether sex-biased maternal investment (contact, grooming, suckling) is associated with socialisation timing of male and female fawns.

Research: The project is based at the Phoenix Park, Dublin where a resident herd of fallow deer have been studied for over 30 years. The deer are tagged as fawns and are, therefore, uniquely identifiable. Working with this population, the student will join a research group of QUB postgraduate students and academics, to study the doe herd during July and August.

Learning: The student will be trained in behavioural data collection including core sampling and recording techniques in the field; specifically, they will learn to record doe presence/absence and fawn presence, contact between mother-fawn pairs (e.g. grooming and proximity), and the frequency and duration of suckling bouts. Following data collection, they will learn how to handle and process these data, ultimately learning how to analyse and interpret the data using generalised modelling techniques.

Title: From the dancefloor to dancing bots: understanding spatial organization of honeybee colonies using Kilobots

Lead Supervisor: Fabio Manfredini (fabio.manfredini@abdn.ac.uk), University of Aberdeen, School of Biological Sciences

Second Supervisor: Elena Giannaccini (elena.giannaccini@abdn.ac.uk), University of Aberdeen, School of Biological Sciences

Discipline: Behavioural Ecology

Proposed start date: 13/06/2022

Proposed working pattern: approx. 18-19h/w over 10 weeks (total of 189 hours)

All the experimental work associated with this project will take place on campus at the University of Aberdeen. Please consider this when applying since the budget for research costs, including travel, is limited.

Project description: 

Honeybees are among the most efficient insect pollinators and for sure they are the most significant in terms of impact on human economy. In addition, honeybees represent the apex of the evolution of social behaviour. One of the most intriguing behaviour is the waggle dance communication, a series of stereotyped movements that bee foragers perform in the hive to share information with nestmates about the of a profitable food source or a new nesting site. The waggle dance is one of the most complex examples of communication in the animal kingdom, and it has been extensively studied at multiple levels, considering the evolution, the ecological relevance and the biological processes that underpin it – a core part of the ongoing research in Dr Manfredini’s research group (Veiner et al. 2022, Manfredini et al. in prep.). Nevertheless, we still lack a thorough understanding of how an insect can incorporate a rather complex piece of information in a series of simple movements that can be shared socially with other nestmates.

The aim of this project is to use robotics to address this long-standing question in biology from a completely different and new point of view. In collaboration with Dr Giannaccini’s team we propose to use Kilobots, a ground-breaking Harvard-designed swarm robotics platform (Rubenstein et al., 2012), to recreate in a controlled environment the movements and the network of social interactions that honeybees perform during the waggle dance. The student will start from empirical observations of the interactions between dancers and dance-followers directly on the dancefloor (Objective 1), thanks to observation hives that have been specifically purchased for this purpose and will be installed in the University of Aberdeen campus in May. Observational data will be used to implement algorithm models that will recreate a similar range of movements in Kilobots (Objective 2) and will test different dance communication patterns, with the aim to identify the most effective solution (Objective 3). Kilobots have already been used to implement a fully distributed collective decision-making strategy that only requires agents with minimal capabilities. However, previous decision-making strategies were loosely inspired by the waggle dance communication language (Valentini et al., 2016). The final step in this project will be to compare the model implemented with the Kilobots to biological data from the dancefloor (real observations and/or video recordings of the dancefloor) to test whether the predictions are fully supported in an ecological framework (Objective 4).

References
Manfredini, F., Wurm, Y., Sumner, S. and Leadbeater, E. Transcriptomic responses to location learning by honeybee dancers are partly mirrored in the brains of dance-followers. In preparation for submission to Current Biology.

Rubenstein, M., Ahler, C. and Nagpal, R., 2012, May. Kilobot: A low cost scalable robot system for collective behaviors. In 2012 IEEE International Conference on Robotics and Automation (pp. 3293-3298). IEEE.

Valentini, G., Ferrante, E., Hamann, H. and Dorigo, M., 2016. Collective decision with 100 Kilobots: Speed versus accuracy in binary discrimination problems. Autonomous agents and multi-agent systems, 30(3), pp.553-580.

Veiner, M., Morimoto, J., Leadbeater, E., & Manfredini, F. (2022). Machine Learning models identify gene predictors of waggle dance behaviour in honeybees. Accepted in Molecular Ecology Resources.

Title: Climate change impacts on social networks

Lead Supervisor: Vasilis Louca (v.louca@abdn.ac.uk), University of Aberdeen, School of Biological Sciences

Second Supervisor: David Fisher (david.fisher@abdn.ac.uk), University of Aberdeen, School of Biological Sciences

Discipline: Ecology

Proposed start date: 01/06/2022

Proposed working pattern: 20h/w over 8 weeks (total 160h)

Laboratory collection will take place in the controlled conditions laboratory (G30), in the Zoology building, University of Aberdeen. Please consider this when applying since the budget for research costs, including travel, is limited.

Project description:

Animal social interactions are important for various aspects of animals’ lives, such as when competing for food and finding mates. These social interactions can be quantified as a network, and social network analysis used to quantify the social phenotypes of individuals and groups. Animals typically use social interactions as a means of buffering environmental stress, and so different environments should favour different social network structures. Global climate change is expected to lead to more extreme weather patterns, higher temperatures and higher, or lower rainfall and humidity levels in different parts of the planet. However, we have a limited idea of how animal social network structure responds to these changes. In this project the student will expose groups of the gregarious cockroach Blaptica dubia, under laboratory conditions, to differing levels of temperature and humidity and record and analyse how their social networks change in response. Following this we can explore the role social network position plays in gaining access to hydration to determine how social and competitive behaviour interact in this species. The selected student will receive training in study design, social network analysis as well as statistical analyses in R.

Title: Macroalgal detritus and food-web subsidies in a temperate Scottish fjord

Lead Supervisor: Ursula Witte (u.witte@abdn.ac.uk), University of Aberdeen, School of Biological Sciences

Second Supervisor: Anton Kuech (a.kuech.20@abdn.ac.uk), University of Aberdeen, School of Biological Sciences

Discipline: Biological Oceanography

Proposed start date: 18/07/2022

Proposed working pattern: 20h/w over 9 weeks (total 180h)

Adequate working facilities for sediment core data collection will be provided in lab G26 (Cruickshank Building, University of Aberdeen campus). This is expected to take approximately four weeks. The fieldwork component is optional and will depend on the students’ interests and covid restrictions. Fieldwork at Ythan Estuary (1-2 days; no accommodation required). Fieldwork at Loch Creran (1-2 days; accommodation required). Please consider this when applying since the budget for research costs, including travel, is limited.

Project description:

Coastal ecosystems are recognised to be able to sequester CO2 on geological timescales, a process referred to as Blue Carbon. Although macroalgae (MA) are dominant coastal primary producers and highly productive, they have been excluded from most Blue Carbon estimates as most of the biomass produced is exported and potentially accumulating at greater depths. Fjords have recently been estimated to be responsible for ~11% of the global oceanic carbon sequestration, and investigations in Arctic fjords have shown that MA-detritus can constitute both an important food subsidy for deep fjord benthos and a significant contributor to fjordic sedimentary carbon stores.

This project will contribute to the baseline understanding of how a largely unaccounted for Blue Carbon source, macroalgal detritus, is utilised by benthic macrofaunal communities and stored in sediments in Scottish fjords. It will build upon prior work on fjordic carbon budgets and quantify for the first time the contribution of macroalgal carbon as a food subsidy for deep benthic communities in a temperate fjord. Samples for the project will be collected in April and May, ensuring extensive laboratory work and training can be performed during the project. There will also be an opportunity for the student to take samples from the Ythan Estuary and Loch Creran to gather an understanding of the sampling involved (sediment cores and oceanographic equipment deployments).

The project has two main objectives:
I. Assessing the amount of macroalgal detritus exported to the benthos via video footage
II. Quantifying the proportion of macroalgal carbon contributing to macrofaunal diets via C and N isotope signatures and stable isotope mixing models.

Skills in collecting, analysing and processing data from video surveys in Loch Creran will be acquired by the student. They will also be trained in the use of a geographic information systems (ArcGIS) to collate the data and creating the 2D model.

The student will also investigate the benthic macrofaunal community structure and food web. This will include training in taxonomic identification of macrofauna and preparation for 13C and 15N stable isotope analysis. Depending on the student interests, there will be the possibility of developing an understanding of the technical aspects involved with the isotope-ratio mass spectrometry, with the analysis performed within the School of Biological Sciences by Nicole Cochrane. Stable isotope analysis is a powerful tool in ecology for elucidating food webs and primary producer source. In addition to the macrofaunal community structure analysis, stable isotope results will be incorporated into Bayesian isotope mixing models (Stable Isotope Analysis in R, SIAR). Depending on the statistical experience and interests of the student, further analyses of stable isotope signatures could be performed to plot Euclidean distances of samples within the sites to calculate trophic structure metrics (MATLAB).

Over the course of the project, the student will develop a range of valuable ecological skills, including extracting data from video material and statistical analysis of extracted data (GIS), laboratory skills in analysing biological samples (systematics and taxonomy), sample preparation for stable isotope analysis and applying isotope signatures to statistical mixing models.

Title: Using Machine Learning to reduce localisation errors for automated radiotelemetry systems

Lead Supervisor: Justin Travis (justin.travis@abdn.ac.uk), University of Aberdeen, School of Biological Sciences

Discipline: Ecology

Proposed start date: 02/06/2022

Proposed working pattern: flexible, 6-10 weeks (189h total)

This project can be carried out from the University of Aberdeen campus or remotely.

Project description:

The project’s objective is developing a prototype approach for using machine learning approaches to reduce localisation errors associated with sensors in terrestrial, automated-telemetry systems. These systems offer huge potential for providing cost-effective data on the movement of large numbers of animals. However, to make the most of the potential, it is important that methods are developed to reduce localisation errors, which are currently higher than ideal. In recent years, ML approaches have been successfully applied to reduce localisation error for sensors placed on fish within grids of acoustic sensors. In this project, we want to utilise similar approaches for a terrestrial system. Calibration data for a pilot system established in the Paramo ecosystem in Colombia has already been collected and more can be collected, as required, to improve the ML fitting. We also have a separate bluetooth-based system that can be tested in Aberdeen and can provide additional scope for both fitting and for field work.

We are seeking someone with interest and experience of applying ML approaches in the environmental sciences. We will provide training in the ecological context in which the technology is used and the potential questions that it can help to address. The student will be embedded within a, large active research group applying a range of computation methods and will this be exposed to a broad range of work at the computer science – biology interface. We have one PHD student in the group who works on ML and AI and they will be able to provide training in some cutting-edge programming approaches in python, if required.

Title: Morphological analysis of volcanic glass as a method of reconstructing eruption processes

Lead Supervisor: Gill Plunkett (g.plunkett@qub.ac.uk), Queen’s University Belfast, School of Natural & Built Environment

Discipline: Archaeology-Palaeoecology

Proposed start date: 01/06/2022

Proposed working pattern: 30h/w over 6 weeks (total 189h)

This project can be carried out from the Queen’s University Belfast of Aberdeen campus or remotely.

Data collection will take place on the campus of Queen’s University Belfast. Please consider this when applying since the budget for research costs, including travel, is limited.

Project description:

The aim of the project is to investigate if volcanic ash shard morphology (e.g., size, shape, fragmentation) can be reliably used to infer eruption processes. The student will examine tephra samples from known eruptions (from the QUB tephra collection) using a high-powered microscope, and will quantify the samples in terms of shard size range and morphology using standard classification techniques. The student will create a photographic library to demonstrate the degree of shard morphological variability within and between samples. The student will gather information from published sources and online resources about the eruptions that produced the ash to determine if different types of eruption can be correlated with a specific type of volcanic ash (for example, effusive, explosive or phreatomagmatic eruptions). If correlations between shard classification and eruption types are found, the method promises to enable inferences about past eruptions known only from cryptotephra deposits. The project has scope to be later developed into a PhD research project subject to the methodological potential being demonstrated.

Title: Which plants were burnt? Exploring the charcoal morphologies of peat forming plants in Finland

Lead Supervisor: Dmitri Mauquoy (d.mauquoy@abdn.ac.uk), University of Aberdeen, School of Geosciences

Second Supervisor: David Muirhead (dmuirhead@abdn.ac.uk), University of Aberdeen, School of Geosciences

Discipline: Geography

Proposed start date: 01/08/2022

Proposed working pattern: 16h/w over 10 weeks (total 160h)

This project includes a strong practical component, as there is fieldwork planned in Finland (up to ~2 weeks). There will also be lab work completed in university facilities on campus. Please consider this when applying since the budget for research costs, including travel, is limited.

Project description:

Fire is a fundamental ecological process but there are still many frontiers to be explored, one of these is the ability to identify which plants burnt at specific moments in time. Past fire frequency and spatial extent can be estimated by counting charcoal fragments preserved in a number of palaeoenvironmental archive records, but reconstructions of which plants burnt through time are still rare. The ability to detect this is important, as the fire intensity is dependent upon the fuel type.
For this study we will focus upon the collection of a series of surface vegetation samples from peatlands in northern and southern Finland, as these are a large terrestrial carbon store and are experiencing more frequent fires due to rising atmospheric temperatures, shifting rainfall patterns and anthropogenic disturbance. We’ll then run a series of novel experimental burn treatments for these samples using a newly designed tube furnace housed in the Geology Department. The objectives of these burning experiments are to:

Objectives
i. Collect mosses, dwarf shrubs and graminoids from a series of peatlands in northern and southern Finland
ii. Undertake burning experiments for a range of mosses, dwarf shrubs and graminoids using the inert atmosphere (nitrogen) tube furnace at temperatures of 250, 400, 600, 800°C
iii. Explore the morphology (including image analysis) and the surface features of the charcoal produced
iv. Create a morphotype classification of the charcoal

Title: Uncovering the seismic signal of the environment in eastern Scotland

Lead Supervisor: Amy Gilligan (amy.gilligan@abdn.ac.uk), University of Aberdeen, School of Geosciences

Discipline: Geophysics

Proposed start date: 20/06/2022

Proposed working pattern: 18h/w over 10 weeks (total 180h)

This project includes a strong practical component, as there is fieldwork planned in several locations across NE Scotland. The remaining work will be complete on campus at the University of Aberdeen. Please consider this when applying since the budget for research costs, including travel, is limited.

Project description:

In this project the student will be working to characterise the seismic signal of environmental and anthropogenic processes in eastern Scotland using data from the newly deployed PICTS (Probing Into the Crust Through eastern Scotland) seismometer network, raspberry shake seismometers and the British Geological Survey (BGS) permanent seismic network. The PICTS network, the first of its kind in north east Scotland, is a deployment of 12 broadband seismometers which crosses the Highland Boundary Fault, one of the main geological boundaries in Scotland, with the aim of uncovering the deep structure beneath the fault and any earthquakes that may be happening.

The first stage of the research experience placement will involve the student participating in fieldwork to collect passive seismic data that the PICTS seismometers have been recording and maintenance of the seismometer installations. They will receive training and experience in how seismometers are deployed in the field. They will be involved in archiving the PICTS data for analysis and in initial data quality control. They will further download publicly available data for raspberry shake and BGS seismometers in eastern Scotland.

The second stage of the placement will involve computing power spectral densities (PSDs) for all seismometers deployed in eastern Scotland, to investigate the spatial and temporal variation in the signals recorded on these instruments. At high frequencies, the signals recorded would be anticipated to be primarily affected by anthropogenic causes, such as traffic and farming activities, and vary significantly from site to site. Lower frequencies may give insights into environmental processes such as wind, waves, and rivers and quantitative comparison can be made with other data sources, such as weather records, to help interpret the results made. For example, it will be possible to correlate periods of high seismic ‘noise’ with named storms and characterise the frequency content of the effect these weather events have on the solid Earth. In this part of the project the student will develop their quantitative data analysis, data visualisation, map making and coding skills.

The successful applicant will visit the locations where PICTS seismometers are deployed in North East Scotland as part of the first service run. These are on 3 NW-SE trending transects in Perthshire (from near Inchure to Glen Fearnach), Angus (from near Crombie Country Park to Glen Doll) and Aberdeenshire (from Benholm Castle to near Tarland). It is anticipated this will take place over 3-4 days between 27 June and 7 July 2022. The local nature of the field locations means there can be some flexibility to ensure that weather is favourable for fieldwork.

Title: Microplastic distribution in the Gulf of Cadiz

Lead Supervisor: Rachel Brackenridge (rachel.brackenridge@abdn.ac.uk), University of Aberdeen, School of Geosciences

Discipline: Sedimentology, geoscience

Proposed start date: 06/06/2022

Proposed working pattern: 20h/w over 7 weeks (total c. 140h)

This project includes a practical component of lab work to be completed on campus at the University of Aberdeen. Please consider this when applying since the budget for research costs, including travel, is limited.

Project description:

99% of the global marine plastic budget is unaccounted for in known surface waste patches. It is therefore thought that large volumes of waste are accumulating in the deep ocean. However, little is known of the source to sink cycle of plastics in deep marine settings. Recent research shows sediments deposited by deep ocean currents (named contourites) are potential hot spots for deposition. However, little is known about which parts of these depositional systems are most plastic-prone and the ocean current velocities that favour microplastic accumulation in deep marine sediments.

This interdisciplinary study applies sedimentological techniques to address an environmental problem. It aims to assess if legacy sediment cores can be used to examine how different geological and oceanographic processes control the deposition of microplastics. The Gulf of Cadiz, offshore Spain, is regarded as the premier natural laboratory for the study of contourite sediments. As a result, an extensive collection of legacy sediment cores have been acquired over the last decades. Sediment samples have been collected over the entire region, from water depths of 600 m to over 2000 m. They sample a wide variety of depositional environments, from those influenced by ocean currents, those dominated by downslope gravity deposit and those influenced by pelagic settling through the water column. As such, the region is an ideal test case for understanding the distribution of microplastics in the marine realm.

This study aims to integrate grainsize analysis of sea bed samples with microplastic analysis and spatial mapping in order to understand microplastic concentration may be linked to depositional processes. The student undertaking this work will have the opportunity to conduct laboratory research and microscope work, as well as developing mapping skills in ArcGIS software. Statistical analysis of sediment data will be completed. Training will be provided in lab workflows and software. The key deliverable will be a poster presenting the findings of the study.

The project will involve laboratory work to extract microplastics from sediment, conduct sediment grainsize and microscope work to describe sediment and microplastics. Lab work will include:

1. Grainsize analysis of sediment samples from across the GOC using laser particle analyzer to reconstruct current velocity.
2. Microplastic extraction in the lab of sea bed samples (St Mary’s Building).
3. Microplastic extraction of subsurface sediment samples across three cores sites to understand the rate of burial of microplastics where influenced by different depositional environments (St Mary’s Building).
4. Microplastic identification (nature, composition) using microscope and Raman spectroscopy (Meston Building).

Results will be compiled using excel and statistical analysis completed. Spatial mapping of results will also be completed using ArcGIS. The key deliverable will be a poster presenting the key findings of the study.

Previous project catalogues

Addressing food security through data and innovation: analysing the effectiveness of a novel fruit fly trap for small farmers in a developing country supervised by Juliano Morimoto & David Fisher, School of Biological Sciences, University of Aberdeen

Quantitative methods for authentication of Scottish tea supervised by David Burslem & Tassos Koidis, School of Biological Sciences, University of Aberdeen

Behaviour and growth in fallow deer fawns supervised by Isabella Capellini & Domhnall Jennings, School of Biological Sciences, Queen’s University Belfast

ARCZero: 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 supervised by Paul Williams & Nigel Scollan, School of Biological Sciences, Queen’s University Belfast

Investigation of inter-annual, seasonal and diurnal variability in pollen rain supervised by Gill Plunkett & Lisa Coyle McClung, School of Natural & Built Environment, Queen’s University Belfast

Discovery of interactions between river properties and bridges within built infrastructure supervised by Myra Lydon & Jenny McKinley, School of Natural & Built Environment, Queen’s University Belfast

Investigating the relationship between climatological variables and the timing of lake and river ice phenology supervised by Andrew Newton & Donal Mullan, School of Natural & Built Environment, Queen’s University Belfast

Understanding the distribution of thermokarst lakes across the Himalaya supervised by Anshuman Bhardwaj & Lydia Sam, School of Geosciences, University of Aberdeen

Implementing a Machine Learning Approach for the understanding of social learning in honeybee foragers supervised by Fabio Manfredini and Juliano Morimoto, School of Biological Sciences, University of Aberdeen

Modelling historical ice phenology data and implications for future environmental change supervised by Andrew Newton and Donal Mullan, School of Natural and Built Environment, Queen’s University Belfast

Assessing the long-term impact of climatic variables on coastal changes in Scotland using geospatial tools supervised by Anshuman Bhardwaj and Lydia Sam, School of Geosciences, University of Aberdeen

Climate change and the future viability of Europe’s longest Ice Road supervised by Donal Mullan and Andrew Newton, School of Natural and Built Environment, Queen’s University Belfast

Geostatistical analysis of spatiotemporal trends of COVID-19 spread in UK supervised by Lydia Sam and Anshuman Bhardwaj, School of Geosciences, University of Aberdeen

Testimonials

“Hi! I’m a Psychology student going into my final year at Queens University Belfast. Seeing this placement advertised on the Queens University career’s website immediately sparked my interest. The title of the summer project I worked on was ‘To examine growth rates in fallow fawns’.

During the ten-week project I learned a variety of skills that will be of huge benefit to me for the rest of my career. I learned how to use expensive camera equipment in order to take the correct shots of the ever-fleeting fawns! I recorded the distance of the fawns using a range finder, the tags of the fawn I photographed and the part of the fawn I captured (the rump or the flank), each time I took a photograph. Working in Phoenix park over the summer months learning about the fawns behaviour patterns, the mother-fawn relationships and human-deer relationship was something that was truly fascinating in an amazing learning environment.

Getting to work alongside two highly experienced PhD students really enhanced my knowledge. They knew so much about the deer as they had studied them throughout the past year, along with having an extensive knowledge about zoology and biology with both sharing their incredible experiences working with animals in South Africa and Australia among others! Along with sharing their experiences they really helped me get settled into the project and were there each week to assist me with anything I needed. I really enjoyed working with these students and they have really inspired me with their dedication and real passion for their projects.

This placement has really inspired me to pursue work in environmental and behavioural research after I complete my degree. It was a really amazing summer placement and I enjoyed every minute of it!”

“I’m a BSc Conservation Biology student at the University of Aberdeen, entering into my second year of study. I had the opportunity over the summer of 2021 to participate in the project “Investigating the relationship between climatological variables and the timing of lake and river ice phenology”.

I have a big interest in the environment and the challenges it faces whilst also having some previous experience in geography. I was therefore intrigued by the project and how it seemed to give me an opportunity to combine my interest in the environment whilst further exploring geography and ice phenology.

During the project I got to compose data of freeze-up and breakup dates of ice on lakes and rivers in the northern hemisphere. I then calculated the correlations between that data and temperature data from the surrounding locations. These correlations will be used to see how different climatic variables affect lake and river ice across the northern hemisphere.

I have found this opportunity to be a fun challenge and a valuable experience for my continued studies. By learning more about what conducting a research project entails and by giving me a broader understanding of the environmental challenges we face, it has encouraged me to follow down the research path.”

“Hi! As a Geography and International Relations student at the University of Aberdeen, I am interested in the relationships between people and the environment. Interdisciplinary approaches are key when addressing these relationships. Because of this, I was very excited about the opportunity to work with researchers from the School of Biological Sciences on the project called: “Addressing food security through data and innovation: analysing the effectiveness of a novel fruit fly trap for small farmers in a developing country.

During this placement, I analysed the field trial dataset provided by the industry partner to assess the performance of the new trap (that captures both male and female fruit flies) compared to the standard traps (that attract only male flies). To do this, we conducted statistical tests – such as mixed effects modelling – using the programming language R. We also developed predictive models to understand the influence of the fruit fly trap on future fly populations. We have been working on presenting these findings in a peer-review publication that will be submitted later in this year.

The project gave me the chance to strengthen my quantitative skills while contributing to research that would help small-scale farmers understand the potential economic benefits of this new trap. I can confidently say that this experience has been immensely invaluable and has encouraged me to explore a career in research.”

“As I am going into my second year of my BSc Architecture degree at the Queen’s University Belfast, I wanted to further explore the environmental side within the built environment. By getting actively involved in the project called “ARCZero – Accelerating Ruminant Carbon towards Net Zero Carbon Farming” – I was able to do so.

Throughout the course of the project, I had the opportunity to experience fieldwork to take soil samples which I would then process in the laboratories. With that being done, I was closely working together with other researchers, industrial partners, and project leaders, with whom I attended various meetings. After a few weeks, the first results from the carbon analysis from a laboratory in England came in and I was able to build up a master spreadsheet featuring the variety of soil properties between the different samples.

Besides, there has been a strong interdisciplinary aspect in terms of initiating a conversation between the two departments of Architecture and Biological Sciences. It was my pleasure to set up meetings with Architecture staff at Queen’s to discuss potentials of linking the project with the built environment to properly inform design solutions. Ultimately, this has certainly been one of the most enriching experiences I have had so far, and I am especially looking forward to how this project will be progressing and when it will be presented at the COP26 in Glasgow!”

Read more about Charlotte’s project on the QUADRAT blog.

“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.”

FAQ's

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 sbsinternships@abdn.ac.uk 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.

The scheme dictates that you must be completing your first undergraduate degree in order to be eligible, however a change of degree programme does not disqualify you from applying, provided you did not complete the previous degree you started.

If you did complete a previous undergraduate degree, and you are currently studying for your second undergraduate degree, you are not eligible to apply.

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+
6 weeks £1,456.32  £1,855.92 £1,978.02
8 weeks  £1,941.76 £2,474.56 £2,637.36
10 weeks  £2,427.20 £3,093.20 £3,296.7

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 quadrat@abdn.ac.uk 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 infohub@abdn.ac.uk 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 right to work check will be undertaken to confirm successful candidates’ eligibility to work in the UK. This is an HR process whereby we are required to request a copy of your passport and arrange a short call with you to confirm your identity. 

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.