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NERC Funded Research Experience Placements (REPs)

The Natural Environment Research Council (NERC) is offering level 2 and 3 (and 4 in the case of integrated masters) undergraduate students (first and final year students are not eligible) from quantitative disciplines outside of the NERC science remit, the opportunity to do a paid summer (remote) placement working on one of nine research projects within the environmental sciences (titles and details below).

Three 6-10 week funded placements are available for completion over the summer of 2020. All placements have been designed for remote delivery.

For a brief introduction to the NERC REPs scheme and QUADRAT DTP please view our panopto presentation.

FAQs can be found at the bottom of this page.

FUNDING
A salary of up to £2,000 is available at the National Living Wage. A further £500 will be available for project research and training expenses.

ELIGIBILITY

The REP scheme is not open to students already studying within NERC’s science remit (e.g. biological sciences, environmental sciences, geography, geoscience, archaeology etc). Applicants must meet all of the eligibility criteria below:

• Be a current registered student at the University of Aberdeen or Queen’s University Belfast.
• Be studying for an undergraduate degree in a quantitative discipline e.g. mathematics, statistics, computing, engineering, physics, chemistry (outside of NERC’s science remit).
• Be applying for a placement in a different school/department to their undergraduate degree. Where multiple disciplines sit within one school (e.g. QUB SNBE) candidates can apply to a project within the same school provided it is within a different discipline to that which they study e.g. an Engineering student can apply for a project within Geography.
• Be undertaking their first undergraduate degree studies (or integrated Masters). First and final year UG students are not eligible to apply (you cannot be graduating this year).
• Be expected to obtain a first or upper second-class UK honours degree (to be evidenced by email from personal tutor or equivalent or by providing your record card or provisional transcript).
• Fall within the eligibility criteria for NERC PhD students (i.e. be a UK or EU national or have permanent residence / right to remain in the UK). Passport confirmation will be required for successful candidates.

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.

HOW TO APPLY

Candidates are asked to apply for no more than one of the projects listed below. Only your first application will be considered. Please note, candidates are not restricted to applying for a project at their registered institution e.g. a Queen’s student may apply for an Aberdeen project due to remote delivery. Further project details are attached.

Step 1: Please complete this application form: https://app.geckoform.com/public/#/modern/21FO00fiqaqps00078cvj9pmio

Step 2: Please also send your CV and evidence of your expected final grade to sbsinternships@abdn.ac.uk

Please ask your personal tutor to send an email to sbsinternships@abdn.ac.uk with details of your expected grade. This should be sent from their institutional email address. This can be forwarded by the candidate provided the email thread clearly shows the sender details. Alternatively you can provide a copy of your record card or provisional transcript (Aberdeen students can email infohub@abdn.ac.uk for a copy of this).

Please note: you must submit all of the above in time for the deadline for your application to be considered.

DEADLINE TO APPLY: Thursday 11th June 2020 at 23.59 BST

SELECTION PROCESS

The project supervisor will identify the best candidate for their project. These candidates, one per project, will attend a short interview via Microsoft Teams, with three projects/candidates then being supported.

PROJECTS

There is a choice of eight projects to choose from. In all cases supervisors will provide specific training and supervision to complement the skillset and experience of the applicant. Candidates are asked to apply for no more than one project. For any additional information around the project please contact the supervisor directly.

1. Developing parallel computation architecture for running ecological simulations at large spatial extent. Supervised by Professor Justin Travis, School of Biological Sciences, University of Aberdeen.

Project overview: A key challenge with many of the ecological simulations that we conduct is running them both at a fine resolution and at a large spatial extent. The fine resolution is often required to effectively capture key behaviours and interactions with the landscape. The large spatial extent is often required when we are seeking to make large scale forecasts or make management recommendations for large areas.

This project will explore the potential to parallelise our simulations to enable large extent simulations to be run more effectively. In particular, we are keen to explore the potential to parallelise space across a cluster. Populations living on different parts of the landscape would be simulated by different nodes – there would need to be cross talk between nodes probably on an annual time step.

We would train the student in the ecological simulation tools that we apply and give them understanding of the essential biology that they represent. We would also provide exposure to a broad range of key contemporary questions that require the expertise of computation scientists in the ecology/environment sector. The student would be fully integrated within the research team, working closely with members of the team who work on the code development, having meetings with them on at least a twice weekly basis. Depending on their existing skill sets we would provide training in R and/or C++.

Equipment: entirely computer based, computer and internet required.

Candidate skills/background: computer scientist (preferably skilled and interested in using HPC)

2. Implementing a Machine Learning Approach for the understanding of social learning in honeybee foragers. Supervised by Dr Fabio Manfredini, School of Biological Sciences, University of Aberdeen.

Project overview: The project deals with the development of a machine learning approach to characterise the molecular underpinning of social learning in honeybees during the waggle dance. The waggle dance is a fascinating behaviour that honeybees use to communicate the location of a profitable food source to nestmates. This complex behaviour has been studied for long time and since the last century researchers have been successful in characterising all aspects of its regulation at the individual and group level. However, we don’t know much about its fine regulation at the molecular level. In a previous project, we have started to investigate what genes in the brain of the honeybee might underpin the waggle dance communication. We have focused on two groups of bees: the bees that perform the dance (or ‘dancers’) to transfer the information they possess to nestmates, and the bees that attend the dance (or ‘dance followers’) interested in knowing the location of the new food site. In this project, the student will use transcriptomic data obtained from dancers to implement a machine learning approach and test whether it is possible to predict the patterns of brain gene expression in followers that participated in the same dances. Machine learning approaches such as Support Vector Machine (SVM) have been used for different applications in biology, however, it has never been applied to understand how complex behaviour are regulated. This will be a unique opportunity to explore the molecular basis for social learning in a biological system that is an emerging model for the study of complex behaviours. Honeybees are key pollinators for wild flowers as well as for many agricultural crops, hence they provide key ecosystem services to both natural and human-dominated environments. Understanding how the waggle dance communication system is regulated at the fine molecular scale will provide new tools to mediate the negative effects that environmental change is having on these important insects. The student will receive training from the two supervisors in three main area of environmental research: a) the analysis of social behaviour in animals, b) the quantification of gene expression in wild organisms by means of a high throughout approach, and c) the implementation of a machine learning approach to solve a question in evolutionary ecology.

Equipment: entirely computer based, computer and internet required. In case other non-free software or access to more computational power is required, we will arrange for the student to have access to the computer cluster at the Centre for Genome Enabled Biology and Medicine at the University of Aberdeen.

Candidate skills/background: n/a

3. Development of graphical user interface tools for a new model of soil organic matter turnover, organic wastes use, and crop and livestock productivity in low to middle income countries. Supervised by Professor Jo Smith, School of Biological Sciences, University of Aberdeen.

Project overview: The ORATOR model is a systems model, developed at the University of Aberdeen, to understand the impact of different farm management decisions on soils, and crop and livestock productivity. It has so far been applied in a wide number of different countries in Africa and India to look at the sustainability of different farming systems. This work aims to contribute towards alleviating rural poverty, minimizing soil degradation and reducing greenhouse gas emissions.

The model was originally written in Microsoft Excel but has recently been ported into Python. We need an aspiring and thoughtful student to help develop the user interface to the new Python application using the GUI (Graphical user interface) toolkit PyQt5. The objective is to present dynamic charts and tables to the user as well as enabling user control of model settings via standard widgets such as drop-down menus, input fields and check boxes.

In addition to the purely computer/modelling component the student will need to understand the science behind crop production, soil management and livestock inputs and outputs in order to allow the underlying concepts to be clearly communicated to the user. Training will be provided in Systems modelling: specifically the ORATOR model, soil science, agricultural practices in low to middle income countries, use of organic wastes in low to middle income countries.

Equipment: entirely computer based, computer and internet required.

Candidate skills/background: n/a

4. Developing a public database of terrestrial ice caves as analogues for Mars research. Supervised by Professor Javier Martin-Torres, School of Geosciences, University of Aberdeen.

Project overview: The goal of the project is to perform a literature review and compile a database of metrics related to terrestrial ice caves that are potentially relevant as analogues to ice caves on Mars. The supervisors will provide the student with an overview of the state-of-the-art on caves and cave-like features on Mars, and on the current mission proposals by NASA to investigate martian caves in the near future.

The student will assimilate concepts about the environment on Mars, missions to Mars, the importance of Mars analogue studies, and will gain insight into the process of compiling a research database in a clear, structured and rigorous manner. This will be invaluable training for a student who may wish to undertake a PhD in due course.

• Compile a list of known terrestrial ice caves and glacier caves.

• Focus on those caves that are deemed to be particularly relevant in the context of Mars. A systematic review of publications pertaining to these caves. Additional information will be compiled into the database.

• Database organization and formatting: we will work with the student on this but will propose to use XML to format the data.

• Archiving: we will discuss the details of the archiving and subsequent maintenance. For example, issues to discuss include a webserver option, database maintenance etc.

This database will enable the research team to systematically identify the most relevant terrestrial analogues for application to Mars exploration, but it will also be made publicly available and so provide a service to the Mars scientific community.

Equipment: entirely computer based, computer and internet required.

Candidate skills/background: n/a

5. Assessing the long-term impact of climatic variables on coastal changes in Scotland using geospatial tools. Supervised by Dr Anshuman Bhardwaj, School of Geosciences, University of Aberdeen.

Project overview: We propose to use satellite datasets starting from 1970s until present covering nearly 50 years of timespan to observe the coastal changes for Scotland. Dynamic Coast initiative (http://www.dynamiccoast.com/index.html) is a remarkable initiative by the Scottish Government to record the changes in the coast. The expected data proposed to be compiled through our project can be a good value addition to the Dynamic Coast initiative, in terms of quantitative assessment of the long-term climatic variables and its impact on the coastal changes. Such detailed up to date quantitative assessment of the entire Scottish coast is still missing.

The project will have the following research objectives:

• To use multi-temporal and multi-sensor satellite images to delineate the Scottish coast.

• To identify and quantify the changes in the shoreline.

• To derive statistical inferences from long-term meteorological observation and their impact on coastal changes.

This project will benefit from the quantitative skills of the candidate of a statistical, computing or mathematics background. The candidate will be trained on downloading, processing and archiving remote sensing datasets, and subsequently performing geospatial analysis in GIS environment. Thus, the candidate will be able to correlate the statistical inferences drawn from meteorological datasets with geospatial observations to identify the spatiotemporal variability in coastlines. Observing such trends can provide useful inputs to coast modellers for predicting future changes in the wake of changing climate. This project will offer the candidate enough opportunity to apply his/her skills and to take initiative in uniquely analysing time series of climate and Earth observation data.

The student will be trained on handling remote sensing datasets, various remote sensing and GIS software tools, and geospatial analysis. The objective of this project is also to finalise the findings in the form of a research article and the student will be encouraged and trained on taking a lead in drafting and coordinating high impact multi-authored research papers.

Equipment: entirely computer based, computer and internet required.

Candidate skills/background: statistics, computing or mathematics

6. Geostatistical analysis of spatiotemporal trends of COVID-19 spread in UK. Supervised by Dr Lydia Sam, School of Geosciences, University of Aberdeen.

Project overview: The ongoing global pandemic has not just claimed numerous lives worldwide, but has also widely disrupted the economies and societies in general. The world has witnessed increasing number of confirmed cases and mortality rate, the UK in particular has been one of the worst hit countries. The ongoing pandemic has raised several questions which need to be answered. One of the most important of these questions is to identify spatiotemporal and geographic trends in COVID-19 spread to better enable policy makers encountering any such future crisis more effectively.

There are numerous available datasets at global, regional and municipality scales which can be effectively employed to perform such geostatistical analyses using open source software programs, such as QGIS, R statistical package and GeoDa. The proposed research is aimed at providing a holistic overview of the spread of COVID-19 infection across the UK. Such detailed up to date and temporal COVID hotspot assessment for the entire UK is still missing and is needed to resolve the inherent geographical trends.

The project will have the following research objectives:

• To use reliable multi-source COVID-19 data for generating temporal spread maps at different spatial scales.

• To analyse the temporal hotspots in the study area.

• To perform geostatistical simulations for various demographic scenarios.

This project will benefit from the quantitative skills of a candidate with a statistical, computing or mathematics background. The candidate will be trained on downloading, processing and archiving relevant datasets, and subsequently integrating it in GIS environment for further geostatistical analyses, such as, growth rate of COVID-19 cases in UK pre and post lockdown, improvement in recovery rate, and its spatiotemporal spread.

Furthermore, to understand and predict the trend for similar future crisis, there is a need to perform geostatistical simulations for various scenarios, such as population density, implementation and the duration of lockdown, and other mitigation strategies. This can prove to be a useful information for policy makers to effectively implement the mitigation plans in future. This project will offer the candidate enough opportunity to apply his/her skills and to take initiative in uniquely analysing time series of relevant datasets to achieve the proposed objectives.

The student will be trained on handling geospatial datasets, various statistics and GIS tools, and geospatial analysis which will develop their skills in geospatial analyses. The objective of this project is also to finalise the findings in the form of a research article and the student will be encouraged and trained on taking a lead in drafting and coordinating high impact multi-authored research papers.

Equipment: entirely computer based, computer and internet required.

Candidate skills/background: statistics, computing or mathematics

7. Modelling historical ice phenology data and implications for future environmental change. Supervised by Dr Andrew Newton, School of Natural and Built Environment (Geography), Queen’s University Belfast.

Project overview: One of the main controls on hydrological and biogeochemical processes at high latitudes is the freezeup and breakup of lake and river ice. Ice phenology is governed by the geographical setting (heat exchange, wind, precipitation, latitude, and altitude) and the morphometry and heat storage capacity of the water body. The majority of lakes and rivers that seasonally freeze are in the Northern Hemisphere and most research has tended to focus on breakup/freezeup dates, ice season length and ice thickness. However, as is acknowledged by the IPCC, an assessment of changes in broader ice phenology is complicated by, among several factors, the tendency to consider only local areas. The student will be introduced to topics related to climate change more broadly, and then lake and river ice in more detail. This will set the scene for the rationale behind the project and the key aims and objectives. The student will have access to a number of raw datasets that capture environmental data from lakes and rivers captured across the Northern Hemisphere. There are millions of data observations in these datasets and they would benefit significantly from a dedicated study. The student will compile coded projects that organise and interrogate the data to understand the trends and key observations that can be extracted. The expectation is that the statistical analysis will provide a unique insight into environmental change over the last ~500 years. All being well, the student will also be able to play a part in writing up of these results for later publication as a co-author. The student will have access to a supervisory team with expertise on ice physics (Newton) and climate change analysis (Mullan). 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 an appreciation of a key area in environmental change. They will also benefit from new insights into how their underlying expertise can be applied to solving environmental problems that are not traditionally associated with their discipline.

The student will be provided with information and material that will allow them to understand the background (climate change) and rationale for studying a topic such as ice phenology. They will also be provided with training on how to access different environmental datasets (numerical/observational/satellite) and then they will be introduced to different software programs (such as ArcGIS). It is expected that the student will already have a background in coding (R or Matlab) and will then work with the supervisory team to build and develop the statistical analyses that will underpin the research. Once the statistics have been generated they will be provided with training on how to interpret and present those data, as well as formulate a mini research report capturing the workflow and conclusions of the work.

Equipment: entirely computer based, computer and internet required.

Candidate skills/background: mathematically inclined with experience of coding (R or Matlab).

8. Climate change and the future viability of Europe’s longest Ice Road. Supervised by Dr Donal Mullan, School of Natural and Built Environment (Geography), Queen’s University Belfast.

Project overview: In high latitude regions of Europe, ice roads serve as important networks linking communities in isolated areas where no permanent roads exist. Although European ice roads do not operate on the same scale as the economically vital ice roads serving diamond mines in Canada, there are a series of ice roads linking marginalised settlements across Estonia, Finland, Norway, Sweden and Russia. The longest ice road in Europe is the 26.5 km route across the frozen Baltic Sea linking Rohuküla on the Estonian mainland with Heltermaa in the Estonian island of Hiiumaa. The road is typically open from late January to late March, but there are growing concerns that a warming climate will reduce this short season or perhaps even deem it unsafe to have an operational ice road at any time during the winter. This would have a devastating impact on the local communities who rely on these ice roads in winter. With temperatures in the high latitudes warming at a rate in excess of the global mean, the threat of climate change to these marginalised communities is very real and increasingly pressing.

This project aims to address this issue by examining how climate change may impact the long-term viability of Europe’s longest ice road and consequently the local communities dependent on it. A modelling approach will be adopted by running a sea and lake ice model under various different scenarios of future climate change to construct a picture of how the ice road will be affected over the coming decades. The student would be able to make use of user friendly models and existing computer scripts to complete much of this work under the guidance of the supervisors, but will also be encouraged to apply some creativity and innovation beyond instruction; particularly in how to present the findings visually and communicate them to affected stakeholders e.g. local community groups on Hiiumaa island. The work will be scaled in such a way to make this a self-contained project with a beginning, middle and an end; enabling the student to initiate the work and see the project through to its final conclusions and outputs over an eight week period. The student will be a named author on any publications emerging from the work. Training will be provided.

Equipment: entirely computer based, computer and internet required. It may also be possible to provide a laptop if necessary.

Candidate skills/background: n/a

FAQ’s

What is a NERC science subject?

NERC is the Natural Environment Research Council and as such the NERC subjects are the environmental sciences such as biology, biological sciences, ecology, marine biology, soil science, geography and geology, archaeology, atmospheric and polar sciences. For the full description please visit the NERC website.

Which disciplines are eligible?

NERC are explicitly looking for 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.

Can I apply for multiple projects?

Please apply for a maximum of one project. Multiple applications will not be considered.

Do I have to be a registered student at a QUADRAT partner institution?

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.

Are REPs projects paid placements?

A salary of up to £2,000 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.

Are placements full time or part-time? Is there flexibility in the working pattern?

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. Monthly timesheets will be required.

I am a final year UG student and I will have finished my course before the placement starts. Can I still apply?

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. Only 2^nd and 3^rd year students are eligible, and 4^th year students in the case of a 5 year programme such as MEng.

Does a REPs project count towards my Honours project?

Unfortunately, the answer is no. If you are completing your honours project and will graduate this year then you are not eligible to apply.

Can I earn credits towards my degree by completing a REPs placement?

No, the REPs placement is extra-curricular and does not contribute towards your degree but is a valuable experience and opportunity to develop new skills.

My school/department is a combination of NERC and non-NERC disciplines. Am I eligible to apply?

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 discipline) and to projects in other schools. For example, an engineering student based in SNBE could apply for a project within the discipline of Geography, but a Geography student could not.

Do I need to have experience in environmental sciences?

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 where necessary.

Do I need a specific skill set?

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.

Will I get training on the job?

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.

Will I need specialist software or equipment?

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.

Should I contact the supervisor before I apply?

You are not required to contact the supervisor before applying, but you may do so if you have questions about the project content or skills required.

What is the selection process? Will there be an interview?

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 (15-20 minutes) via Microsoft Teams. Once the interviews have been completed, the top 3 candidates will be awarded the project and funding.

How can I evidence my expected grade?

Please ask your personal tutor to email sbsinternships@abdn.ac.uk with this information, from their institutional email address. Students can forward this information on if necessary, provided the original sender details are clear. Alternatively, you can submit a record card or provisional transcript. University of Aberdeen students can download this from their student portal or contact infohub@abdn.ac.uk for this.

Do I need to complete any paperwork to confirm the placement?

It is a NERC requirement that both the candidate and the supervisor complete a brief final report form upon completion of the placement. This form will be provided towards the end of the placement. We also ask that you write a short blog post about your placement experience.

Do I need to provide proof of my nationality?

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).

Notes for Editors