Undergraduate Summer Vacation Studentships 2017

We are now accepting applications – to apply please download the application form HERE, and email it to Dr Elizabeth Hayes, the Centre’s Scientific Manager, (e.hayes@imperial.ac.uk) by 23:59 Sunday 9 April 2017.


Deadline for applications is 23:59 Sunday 9 April 2017

The MRC-PHE Centre for Environment and Health is an internationally recognised centre of excellence for leading cutting edge multidisciplinary research on the health effects of environmental pollutants and the translation of this knowledge to inform national and international policies to improve health. A key component of our Centre’s mission is to train and develop the next generation of research and policy leaders in the environment and health arena. As part of the breadth of training opportunities offered by the Centre, we are pleased to offer undergraduate summer vacation studentships to undertake short (approximately six weeks) research project placements with Centre researchers.

Projects will take place during Summer 2017, at dates to be agreed between the student and supervisor.

A description of the projects available is given below and on the Centre website; applicants should indicate their preference for each project, please ensure you complete this section carefully as this will help decide the projects available to you if successful. Shortlisted applicants will be matched with their preferred projects and interviewed by potential supervisors, either in person or by Skype. Successful applicants will then join that research group to work and study in for the duration of their studentship, gaining valuable research experience and contributing to the work of the group.

A bursary of £200 per week, up to a maximum of six weeks, will be provided to successful applicants, to make a contribution to their living costs for the duration of the research experience.

All awardees are required to submit a report on the work undertaken and how their experience has influenced their career plans.

Research projects available (please click for further details):


Applicants must be at least in their second undergraduate year of study and preference will be given to applicants who do not yet have any research experience and would therefore particularly benefit from working on a summer project. Undergraduate UK/EU students are eligible, international students should confirm their eligibility with the Centre’s Scientific Manager (e.hayes@imperial.ac.uk) before applying. Further guidance on eligibility is available on the Imperial UROP pages.

Candidates should also:

  • have good academic results to date (preferably at 2:1 level or above if you are taking a BSc, or above the 50th centile if you are taking the MBBS);
  • demonstrate an enthusiasm for research.


Applications will be assessed and ranked by a selection panel according to the following criteria:

  • The student’s previous examination results
  • The student’s supporting statement, giving reasons why the application is being made

Applicants may be invited to interview by relevant supervisors; this may be in person or by phone/skype.


Applicants are welcome to contact potential supervisors (listed below) with scientific queries. All other queries should be directed to the Centre’s Scientific Manager, Dr Elizabeth Hayes (e.hayes@imperial.ac.uk).



Title: Applying Machine Learning Models to Improve Risk Prediction Models for Coronary Heart Disease. 

Supervisors: Dr Abbas Dehghan and Dr Sarah Filippi, Department of Epidemiology and Biostatistics, Imperial College London

Project Description: Although cardiovascular disease is largely preventable, it remains the number one cause of mortality and morbidity worldwide. Early identification of individuals who are at high risk of coronary heart disease is important both for clinical practice and public health strategies since the efficacy of the treatment will improve if adequate therapy would be initiated at an earlier stage of the disease. For several decades, the so-called traditional risk factors including age, sex, cholesterol, smoking, hypertension and diabetes have been used to predict the risk of cardiovascular diseases. Despite the extensive use of these risk prediction models, their ;shortcomings are known and improving them is urged. A large body of research is focussed on discovering novel biomarkers that could potentially improve the current risk models. However, the majority of efforts have so far failed or resulted in controversial findings. In the last decade many machine learning algorithms have been developed to solve various prediction and classification problems. Machine learning approaches have successfully been applied for object, speech and handwriting recognition, game playing, online advertisement or robot locomotion. In recent years, a growing number of papers are appearing in the bioinformatics and medical literature that try to apply machine learning techniques in medical diagnosis. In this project we are planning to apply various machine learning models, including the so-called Random Forest algorithm, to develop risk prediction algorithms and compare them with the traditional approaches where risk scores are simply added to each other. Prerequisites: Some knowledge of a statistical programming language such as R would be very beneficial

Contact: Dr Abbas Dehghan: a.dehghan@imperial.ac.uk, Dr Sarah Filippi: s.filippi@imperial.ac.uk


Title: Field campaign of a panel study in China on air pollution and cardio-pulmonary disease.

Supervisors: Dr Queenie Chan (joint Department of Epidemiology and Biostatistics, Imperial College London and Environmental Research Group, King’s College London) and Dr Ben Barratt (Environmental Research Group, King’s College London).

Project Description:  This project presents an exceptional opportunity for the student to gain experience of working in multidisciplinary research environment in urban and rural China a part of an international field research team. The student placement will join the Effects of Air Pollution on Cardio-pulmonary Disease in Urban and Peri-Urban Residents in Beijing (AIRELSS) team for summer field campaign (22 May 2017 to 25 June 2017) in China.  AIRLESS is one of two health based projects funded under the Atmospheric Pollution and Human Health in a Chinese Megacity (APHH) under the NEWTON programme. http://www.nerc.ac.uk/research/funded/programmes/atmospollution/

The student will be part of this UK-China Collaboration working with the research team from King’s College London, Imperial College London, Cambridge University and Peking University.  The student will learn about data collection for a panel study of residents selected from two well established cohorts, INTERMAP and CMCS Studies.  The student will gain research experience in conducting surveys and clinical visits in Beijing. He/she will have the chance to operate portable personal air pollution samplers (Personal Air Quality Monitor [PAM], Cambridge University, UK), indoor black carbon monitors (Aethlabs MA300 and MA350, San Francisco, California, USA) and PM monitors (RTI MicroPEM, Durham, North Carolina, USA).  After the fieldwork, the student will preform data entry/management compliance with the Data Protection Act and Information Governance under the supervision of Dr Chan and Dr Barratt at Environmental Research Group, KCL.  The student will have the opportunity to learn about air pollution modelling (including the assessment of model uncertainty), air quality management and human exposure during the 4-week in London.  The student will also be learning about black carbon filter measurement at the facility at KCL.

Key skills required: Undergraduate studies in environmental science, epidemiology/public health/medical science, or other relevant quantitative sciences; good communication skills in English and Chinese (Mandarin); experience of working in a multidisciplinary research environment in developing countries or with international organisations.

Contact:  Queenie Chan: q.chan@imperial.ac.uk, Ben Barratt: benjamin.barratt@kcl.ac.uk


Title: Linking inflammatory changes at baseline, exacerbation and recovery in Chronic Obstructive Pulmonary Disease (COPD) to environmental exposure. 

Supervisor: Dr Jennifer Quint (National Heart and Lung Institute, Imperial College London)

Project Description: To investigate how changes in environmental exposures may trigger inflammation in the airways leading to an exacerbation, or increase susceptibility to infection, increasing severity and frequency of individual exacerbation episodes. Viral and bacterial detection in sputum will be undertaken using quantitative rt-PCR for human rhinovirus, multiplex rt-PCR for other respiratory viruses and qPCR for S pneumoniae, H influenzae and M catarrhalis. MSD V-PLEX Human biomarker 40-PLEX kit will be used for investigating changes in biomarkers from blood and sputum samples. These lab data will then be linked with environmental data from personal exposure monitors.

Contact: Jenni Quint: j.quint@imperial.ac.uk


Title: Metabolomic evaluation of the effects on vascular function of types of fruits and vegetables. 

Supervisors: Dr Linda Oude Griep and Professor Paul Elliott (Department of Epidemiology and Biostatistics, Imperial College London)

Project Description: Elevated blood pressure is the leading population-wide modifiable risk factor of cardiovascular diseases. Evidence is well-established that improved lifestyle factors lower the risk of CVD through blood pressure lowering effects, for example higher fruit and vegetable consumption. The application of novel metabolomics technologies that detect small molecules in biofluids enables identification of potential urinary biomarkers of types, such as citrus fruits and cruciferous vegetables in small interventions. Such biomarkers help combined with well-established biomarkers of total fruit and vegetable intake e.g. plasma vitamin C and urinary potassium to simultaneously and objectively identify relationships and potential underlying mechanisms with vascular function. In this pilot intervention study among 20 pre-hypertensive individuals, we will validate previously found urinary metabolites related to higher intakes of types of fruits and vegetables on vascular function to further investigate potential underlying mechanisms. These methods and technologies can also potentially be applied to a range of other lifestyle factors that may be implicated in CVD e.g. environmental exposures to investigate the disease mechanisms.

During this summer project you will learn more about:

  • novel technologies to identify small molecules in biofluids
  • the importance of food consumption on cardiovascular health
  • why we do dietary intervention studies and what it involves
  • how these novel technologies can improve epidemiological research

You will gain knowledge and experience in data entry, sample handling, laboratory work, and data analyses. It is preferable if you have some experience in laboratory work or data analyses, but is not essential.

Contact: Dr Linda Oude Griep: l.oude-griep@imperial.ac.uk


Title: Systematic reviews in air quality and health.

Supervisors: Dr Heather Walton (Environmental Research Group, King’s College London)

Project Description: The aim of the project is to complete a systematic literature review extracting and synthesising data on topics relevant to air quality and health. Potential titles are listed below, the student would focus on a subset of the possible work on these subjects. The project would require a critical eye when reviewing literature, ability to extract and synthesise data, experience using online journal search engines and databases, confidence using reference managers such as EndNote. Some basic statistical analysis on the extracted data may be warranted. Students will gain experience and knowledge in conducting a systematic literature review, critical appraisal of literature, data extraction, data synthesis, report writing and statistical analysis.

Potential topics are:

  • Comparing and contrasting the effects of particulate matter and nitrogen dioxide on the respiratory and cardiovascular system in human volunteer studies.
  • Does health impact assessment of increased use of wood stoves need development of specific concentration-response functions or is it reasonable to use the available functions for particulate matter in general?
  • Potential mechanisms for effects of inhaled nitrogen dioxide on cardiovascular disease

Contact: Heather Walton: heather.walton@kcl.ac.uk


Title: Accounting for smoking in epidemiological studies: evaluation of different smoking proxies. 

Supervisors: Dr Anna Freni Sterrantino, Marta Blangiardo and Anna Hansell (Department of Epidemiology and Biostatistics, Imperial College London)

Project Description: Smoking is closely associated with increased risk of disease and worse outcomes. Small area geographical studies which use routinely collected data (e.g. death registrations, hospital admissions) are extensively used in epidemiology, but usually have limited or no information on smoking within the record. For example, the Small Area Health Statistics Unit (SAHSU) used hospital admissions and death registrations to look at associations between aircraft noise and risk of cardiovascular disease in neighbourhoods in London in a BMJ study about health impacts of aircraft noise from Heathrow airport (http://www.bmj.com/content/347/bmj.f5432). Information on smoking prevalence was not available in the health data and also not available for neighbourhoods, so in the BMJ study we used a proxy measure of area-level lung cancer rates. There are other smoking proxies we could use in similar studies but they have not been compared with each other.

This aim of this project will be to investigate how the use of different smoking proxies. The student will look at correlations and geographical patterns of five different smoking proxies: a) smoothed area-level rates of lung cancer mortality, b) CACI area-level expenditure data on tobacco sales, c) population weighted information on smoking from the Integrated Household Survey and d) population weighted information on smoking from the Health Survey for England e) deprivation indices (deprivation is closely associated with smoking prevalence). The student will then conduct analyses of cardio-respiratory hospital admissions and mortality in areas in relation to particulate air pollution (PM10). This part of the study will need to be conducted on-site at SAHSU and the student will be required to do some information governance training to gain permissions to access the SAHSU networks.

Aims of the project:

  • To conduct a literature review of the use of smoking proxies in epidemiological studies and the association of cardio-vascular disease and air pollution in England.
  • To produce descriptive statistics of the potential smoking proxies and look at the correlations between these and area-level confounders such as deprivation.
  • Statistical analyses:
    • Of aggregated data (disease mapping models) including associations of smoking proxies with cardiovascular disease and lung cancer.
    • To compare adjustment for smoking proxies on the association between air pollution and with cardio-respiratory outcomes (cardiovascular disease)
  • To provide a basis for a future publication

This project would suit a student with a strong interest in spatial analysis and in performing and interpreting statistical models. Students will gain knowledge and experience in:

  • literature review and interpretation of studies
  • spatial manipulation of geographical data using R
  • statistical analyses to generate and explore variation in prevalence data in R / BUGS
  • scientific writing

Contact: Anna Freni Sterrantino: a.freni-sterrantino@imperial.ac.uk


Title: Changes over time in socioeconomic status and ethnic profiles of small areas in Great Britain

Supervisors: Dr Daniela Fecht (Department of Epidemiology and Biostatistics, Imperial College London)

Project Description: The release of the 2011 census has revealed substantial differences in ethnic composition of some neighbourhoods compared to previous censuses; changes in socioeconomic status (SES) are more subtle. Both ethnicity and SES are important factors to predict health care provision and resource allocation as well as to identify areas in need of regeneration. It is therefore important to gain knowledge of how ethnic profiles and SES have changed in the past in order to make assumptions about future trends. 

This project uses small-area level data on ethnicity and SES from current (2011) and historical censuses (potentially to the year 1961). Census data will be mapped to the same geographical areas in order to identify changes over time.

The specific aims of the project are to:

  1. Identify data from historic censuses which could be used to characterise ethnic and socioeconomic profiles for small areas in Great Britain;
  2. Compile such data and potentially map them within a geographical information system (GIS); training on the use of GIS will be provided if necessary;
  3. Explore changes in ethnic and socioeconomic profiles over time using basic quantitative methods and statistics.

The project would be suitable for a student wishing to gain knowledge and experience in i) using routine data for analysis, ii) manipulation of large datasets, iii) basic statistical analyses and iv) data visualisation. This project forms part of a wide body of work on health and environmental inequalities and there is potential for a scientific publication depending on outcomes.  

Contact: Dr Daniela Fecht: d.fecht@imperial.ac.uk