Summer REPs 2022

This year we have 5 vacancies for Summer REP students. These short projects (6 - 10 weeks long) are intended to give research experience to students currently undertaking a bachelors degree, who might be considering a further degree.  We are very keen to reach out to students who might not normally think of Oxford as a destination for doctoral study and a summer REP is a perfect way to find out more about Oxford without having to commit just yet.  In order to be eligible, students must be:

In line with our drive to welcome a greater diversity of students to Oxford, we are particularly encouraging applications from students who meet at least one of the following criteria:

  • be in the first generation of your family to go to university;
  • have been in care for at least three months;
  • have been a young carer;
  • belong to an ethnic group under-represented at Oxford (Black or Mixed Black, Bangladeshi or Mixed Bangladeshi, and Pakistani or Mixed Pakistani);
  • be from a low-income background and in receipt of more than the minimum levels of support detailed from your regional funding body; or come from a neighbourhood which is classed as ACORN 4 or 5 or POLAR (4) Quintile 1 or 2 in the final calendar year of their secondary school education.

Academic expectations: Applicants should usually be on track to achieve a final undergraduate (or integrated Masters) degree grade of a strong 2:1 or First.

Preference may be given to those without research experience who will most benefit from the programme.

Students will be paid at at least the minimum wage for the duration of their project and will receive an additional grant, for research costs, of £500.  A report must be completed by teh student and supervisor at the end of the placement.

You can apply for up to 2 projects.  In order to apply, please select the project(s) that you are interested in and complete your application on this online form  by 31st May

Project 1: Incorporating waste water treatment standards into global water quality models

Prof Jim Hall, Dr Razi Sheikholeslami, Olivia Becher, Jasper Verschuur, Oxford University Centre for the Environment

OVERVIEW: A large fraction of global wastewater is being directly discharged into rivers, lakes and the sea. This has serious impacts upon biodiversity and human health. The quality of the wastewater being discharge unto the water bodies depends on the type of treatment (primary, secondary, tertiary) and the associated standards set per country. This depends upon the existence of wastewater treatment plants and the treatment processes that are installed at those plants. As countries develop and urbanize, they tend to invest in expanding wastewater treatment coverage (e.g. the number of households connected to treatment facilities) and also upgrading treatment technologies to more advanced processes.  

So far, it is unclear how the presence of treatment technologies (primary/secondary/tertiary) differs per country as well as the environmental regulations for wastewater discharge. The aim of this project is to collect data and incorporate new understanding of wastewater treatment infrastructure in global analysis of water quality. Our machine-learning based model of water quality already exists, so we would now like to test the effect of improving wastewater treatment infrastructure on water quality globally.  

The student will review literature and collect data across different countries, in particular trying to relate wastewater discharges to a country’s development stage (low/middle/high income) and other factors. The student would write a synthesis on, which could be used for quantitative analysis on future wastewater technologies across countries globally. The data will be used to interpret the current state of water quality in freshwater bodies and make predictions of the effects of future changes in wastewater treatment.  

TIMELINE: The project is divided into three stages: (1) week 1, background reading for water quality and waste water treatment; (2) week 2-4, collect data on wastewater treatment plants and water quality standards across a wide range of geographies; and (3) week 5-6, work with colleagues to implement treatment standards and future scenarios in water quality modelling.  

STUDENT’S INITIATIVE: The student will work with the supervisor to devise ways of characterizing wastewater treatment as national and subnational scales, given inevitable data limitations that the student will find. They will co-develop new methodology for incorporating the data that they find into our water quality model.   


Project 3: What are the impacts of large explosive volcanic eruptions: Revisiting Krakatoa. 

Prof David Pyle, Earth Sciences

The violent volcanic eruption in Tonga in January 2022 reawakened interest in the wider environmental impacts of large eruptions. The Tonga eruption appears to have been one of the most violent eruptions ever observed; and the global impacts, including atmospheric pressure waves and a tsunami that reached all of the world’s oceans, appear to share many parallels with the great eruption of Krakatoa in 1883.  

This summer placement will focus on the similarities between the Krakatoa 1883 and Tonga 2022 eruptions. The approach will be to conduct a systematic retrospective analysis of the Krakatoa eruption, using a systematic review process to survey the peer-reviewed literature; and some archive work to re-examine data collected during and after the Krakatoa eruption. You will then compare these data to the growing literature on the Tonga eruption, and use this to draw some conclusions about the possible short- to medium-term impacts of the Tonga eruption. At the end of the project you will produce a short report detailing the outcomes of your work. 

This project will suit a candidate with a background in Earth Sciences or physical geography, and an interest in data analysis, or the use of historical datasets. This project could be completed either in person, or remotely; and training will be provided in all of the areas required.  




Project 5: Exploring the role of exogenous glycans on the microbial communities of ageing hosts

Dr Kayla King & Prof Rob Salguero-Gomez, Department of Biology (Zoology)

Glycans are key factors governing host – microbe interactions. These biomolecules are abundant in food and are secreted by both host cells and microbes. Gut microbes differ in their capacity to exploit structurally distinct glycans, meaning that glycan availability can be a key driver of microbiota community assembly. Despite the relevance for host health, little is known of how exogenous glycans interact with host ageing to affect microbiota composition. As age-associated changes to metabolism and immunity occur, we hypothesize glycan provisioning will have divergent effects in the microbiota of young and old hosts. To address this question, this project will explore the impact of synthetic glycans on the natural gut community of the nematode worm, Caenorhabditis elegans. Across both young and old hosts, changes in the abundance and diversity of microbial species will be quantified. The implications for host fitness will be assessed by tracking growth rates, survival and reproduction over time. The project will give the candidate an opportunity to fuse aspects of glycobiology, microbial community ecology and ageing research within a tractable model host system, and will further inform on non-invasive control strategies for microbiota. 

Project 2: Global storm risk to coastal cities under climate change

Dr Yu Mo, Prof Jim Hall, Oxford University Centre for the Environment

OVERVIEW: Tropical cyclones, also known as hurricanes, typhoons, or windstorms, cause large losses to coastal cities every year. The storm losses, unfortunately, are expected to further increase as the globally average storm intensity increases in a warmer climate. In addition, the storm risk to coastal cities is highly uncertain owing to the ever-increasing coastal development. The objectives of this project are to (1) assess storm damage using satellite-based Earth observations to better evaluate storm risk, and (2) introduce the student to quantitative skills in physical geography and geospatial data analysis. During the project, the student will, built on existing codes, acquire and process night-time light data (i.e., VIIRS and DMSP) to assess economic loss of storm events over the past few decades; and collect and verify reported social-economic data to validate the satellite measurements.  

Potential areas of interest include Small Island Developing States (SIDS) in the Indian Ocean and the Pacific. The data analysis will be performed with the Google Earth Engine, a cutting-edge cloud-based platform for planetary-scale geospatial data storage.  

TIMELINE: The project is divided into three stages: (1) week 1-2, background reading for storm damage assessment and learning example codes; (2) week 3-4, collect and validate new data datasets; and (3) week 5-6, data analysis and report generation.  

STUDENT’S INITIATIVE: The student will work with the supervisor to choose the study’s region of interest and the satellite datasets to be studied. The student will also be free to choose the format of the final report. For example, it can be a report focus on a statistical analysis of the data or a novel form of data visualization. The student will also be encouraged to submit the report to a conference and to be a co-author of a peer-review journal article.   

  • Any pre-requisites that you expect of the student 

A willingness and aptitude to learn tools and computer codes for analysis of big datasets.   





Project 4: Assessing the dynamics of seal-fishery interactions in the UK  

Dr Katrina David, Department of Biology (Zoology)

As apex predators, marine mammals play important regulatory roles in marine systems. Following protective legislation in the 20th century, many marine species’ populations have recovered from human exploitation. Increases in these populations has increased the spatial overlap of foraging and global-fisheries areas—leading to negative economic outcomes for fisheries and conflict with these animals. This is the case in the UK, where grey seal populations have increased under protective legislation and now negatively impact UK fisheries. With 33% of fish stocks overfished, and fish consumption growing by 1.5% per year, conflict between marine mammals and fisheries is likely to increase. This research is motivated by the need to identify the economic impact of grey seals on UK fisheries, and how this impact is affected by fishery and seal population characteristics. Global reports of fisheries losses incurred by seal depredation remain anecdotal, with no understanding of the economic impacts of these losses or their drivers. Without this information, policy organisations like DEFRA are unable to understand whether compensation or other seal-mitigation responses are required to support fisheries. This project will develop a mechanistic understanding of the extent and drivers of seal impacts on fisheries, which could include fishery characteristics (gear, target species) and seal population characteristics (location, population size or trend). The project will also initialise a long-term structured population dataset for grey seals in UK waters—for which important data regarding rates of growth, survival and reproduction are missing. This is an exciting and timely research area because unravelling the workings of this social-ecological system will help achieve better conservation outcomes while improving people’s income and living conditions. 


Project 6: Synthesis and public database of multiple-stressor interactions in freshwater ecosystems 

Dr. James Orr and Dr. Michelle Jackson, Department of Biology (Zoology)

Freshwater ecosystems are central to our existence but they are being crippled by a huge diversity of anthropogenic stressors. The devastating ecological impacts of pesticides like Roundup, harmful algal blooms caused by excess nutrients, invasive species like the Zebra mussel, and heat waves associated with climate change all regularly make headline news. Freshwater ecologists have invested a huge amount of effort towards understanding the mechanisms of these stressors individually. Unfortunately, in a multiple-stressor world, knowing the individual effects of each stressor isn’t sufficient for accurate prediction of their combined impacts. This is because stressors that co-occur in time and space can interact with each other in complex ways. For instance, many invasive species become far more harmful to native species under warmer climates. Chemical reactions between multiple pesticides can create lethal cocktails that aren’t predicted by traditional risk assessments. There is even evidence that many pollutants can become attached to microplastics, making their combination more toxic than just the sum of their individual effects alone. A major challenge for freshwater ecologists and conservation biologists is to understand the mechanism underpinning all of these stressor interactions so that accurate predictions can be made about their combined effects.  

We recently searched the literature using a novel machine learning tool to find freshwater multiple-stressor experiments. Based on previous traditional literature reviews, we expected to find about 200 relevant publications. Remarkably, we’ve found over 3000! This unexpected and exciting result has presented us with a novel challenge: we currently don’t have the time to screen and collect data from all these papers by ourselves. For accuracy and efficiency, the full text screening, which requires constant dialogue and cross-validation, must be performed by a small group of researchers who can dedicate their time to the project. We are therefore looking for a research assistant to help us screen and collect data from these publications for six to eight weeks during the summer of 2022. The research assistant will also get the opportunity to collaborate with us on an exciting freshwater multiple-stressor experiment being conducted this summer at the University of Oxford’s field station in Wytham. There is also potential to learn about the exciting tools, like flow imaging microscopy, that we use in the laboratory to understand how ecological communities are being impacted by multiple stressors. Finally, towards the end of the placement, the research assistant will collaborate with us on the development of a web-based interactive public database of multiple stressors in freshwaters based on our screening work.