Job description

In October 2020 Sir Patrick Vallance, UK Chief Scientific Adviser, announced the commencement of the National Core Studies as part of the UK’s response to the COVID-19 pandemic. Since the announcement six National Core Studies (NCS) have been established, focusing on key areas in which the UK needed to increase research scale to respond to the near term strategic, policy and operational needs. Professor Nish Chaturvedi (Director, MRC LHA) was asked to lead the Longitudinal Health and Wellbeing NCS.  

The Longitudinal Health and Wellbeing (LH&W) NCS aims to understand the impact of COVID-19 on long term health to inform the design of mitigating policies by bringing together information from existing studies, cohorts, and electronic health records.  

King’s College London is a partner of this project with others including University College London, Bristol, Edinburgh, Glasgow, Swansea, Cambridge, the London School for Hygiene and Tropical Medicine and Bradford Institute for Health Research.  

Each institution co-ordinates a team of Research Analysts across partner institutions interrogating their local cohort and population linked national electronic health records to generate collective insights into COVID-19 relevant research questions. 

This new post will be primarily focussed on an NIHR-funded grant that will investigate long COVID (also known as ‘ongoing COVID-19’ and ‘post COVID-19 syndrome) – constellations of symptoms which last for many weeks or months in some patients affected by COVID-19. This project will characterise the syndrome, identify risk factors and physiological pathways that predispose individual to longer lasting symptoms, profile the consequences of long COVID for later health and work capabilities, and to help guide patient treatment and support. 

In particular, this role will focus on epidemiological analyses of data from long COVID patients, incorporating extensive phenotypic and biological (genetic, epigenetic and other omics) data. You will lead on analysis of data from patients we have identified within TwinsUK and primary care databases, many of whom will be recalled for deep molecular and clinical phenotyping, e.g. with blood-based -omics assaying and imaging studies. You will also be expected to contribute to other aspects of the collaborative covid research which includes socioeconomic and health outcomes of interventions to control the pandemic. There will also be scope to contribute to, or develop your own, research projects within the wider remit of our Unit. 

The main purpose of this job will be to lead on the analysis of quantitative data from a range of data sources and disciplines. The appointee will join a multidisciplinary team that includes clinical and non-clinical epidemiologists, social scientists, statisticians, bioinformaticians and data scientists. The successful appointee will conduct original research leading to publication. More generally, the appointee will be expected to develop an independent research career and will be supported in doing so.  

This post will suit someone with a background in epidemiology, health informatics, data science, applied biostatistics, or related disciplines such as statistical genetics.  

We are looking for evidence of research experience and conducting quantitative analysis, use of and experience of applying appropriate bioinformatic and statistical techniques to high-dimensional omics datasets and ideally the appointee will have experience of either longitudinal analyses of population-based health studies, i.e. cohorts, and/or analysis of electronic healthcare datasets. 

 

This post will be offered on an a fixed-term contract for 24 months 

This is a full-time post

 

Key responsibilities

Key objectives:  

- Plan research studies, including developing analysis protocols, and conducting analyses. 

- To employ appropriate epidemiological methods and statistical techniques to analyse twin, case-control, and longitudinal data, including genomic data.  

- Produce high-quality research outputs, including writing manuscripts for publication. 

- To engage with the MRC and Wellcome core teams on dissemination and data sharing.  

- To participate in project meetings, including symposia and consortium meetings.  

- Maintain open science practices, e.g., by sharing code and publishing research findings openly. 

- Become aware of all applicable Information Security Policies and to be proficient in the use appropriate security measures to maintain the confidentiality, integrity, and availability of TwinsUK study information 

- Keep appropriate records and write clear and detailed documentation for all work undertaken. 

- Actively follow and promote KCL policies, including Equal Opportunities and Race Equality policies. 

 

Communication & networking:  

- Work collaboratively with other DTR researchers, and become part of the positive research environment within the department 

- Interact with a wider consortium of researchers within the NCS, e.g., via working group teleconferences and collaborative projects 

- To collaborate with other specialised centres of excellence to achieve the highest standard of research and publications 

- For candidates with prior experience, there would be the opportunity to assist with teaching of staff and students in twin analyses.  

- To prepare papers as well as manuscripts, abstracts, and grant applications.  

- To write up results of your own research.  

- To liaise with internal and external research colleagues and support staff on research matters.  

- To make internal and external contacts to develop knowledge and understanding and form relationships for future collaboration.

- To communicate material of a specialist or highly technical nature.  

 

Decision making, planning & problem solving:

- To plan own day to day activity within the framework of the project and co-ordinate own work with that of others to avoid conflict or duplication of effort.  

- To make use of standard research techniques and methods.  

- To design and undertake own training programme (with support of line managers) for any skills required you have yet to develop.   

- To deal with problems which may affect the achievement of research objectives and deadlines.  

- To contribute to collaborative decisions making affecting the work of the team.  

- To identify areas for research, develop new research methods and extend the research portfolio.  

Service delivery:

- To provide answers to specialist queries within the area of statistical analysis within genetic and twin research, providing detailed information and a range of solutions.  

- To deal with internal and external collaborators.  

- To respond to requests for information in accordance with departmental and College policies.  

 

Analysis & research:

- To keep up to date with recent relevant literature in the areas of the interplay of mental and physical health, twin research and computational methods relating to genomic data.  

- To identify areas where further research may be needed.  

- To develop twin analysis skills if not already experienced in these.   

- To analyse and interpret the results of research undertaken and draw conclusions on the outcome.  

- To write manuscripts for publication.  

- To assist in the writing of grant application for future research undertaken within the department.  

 

Teamwork, teaching & learning support:

- To actively participate as a member of multiple teams across different institutions.  

- To collaborate with academic colleagues on areas of shared research interest.  

- To seek out and create opportunities to share learning and expertise across the two cohort teams.  

- To be involved in the assessment of student knowledge and supervision of projects.  

- To demonstrate a willingness to develop personal objectives via regular appraisals with the supervisor.  

 

Sensory/physical demands & work environment:

- Carry out tasks that require the learning of certain skills.  

- Required to be aware of the risks in the work environment.   

 

Pastoral care:

- Always show consideration to others.   

 

The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post.

 
 

Skills, knowledge, and experience

Essential criteria 

1. PhD. Ideally this will be in epidemiology, biostatistics, bioinformatics, or a related population health science.

2. Excellent programming skills that include knowledge of R and/or other programming languages (stata/python/perl/C). 

3. Excellent computational skills and experience with high performance computing clusters

4. Proficient with data cleaning, management, and analysis of large-scale datasets, including using the appropriate statistical methods applying to twin data

5. Experience modelling complex data, e.g. from genetics, imaging or -omics assaying (such as studies using epigenetic/metabolomic/proteomic data)

6. Experience of working with longitudinal datasets.

7. Experience of publishing empirical research findings, reports, or data analysis code.

8. Ability to communicate effectively at all levels in a complex multi-disciplinary environment with the ability to produce concise verbal and written reports

9. Ability to work on own initiative and meet competing and demanding deadlines  

 

Desirable criteria 

1. Experience with the development and implementation of records linkage and harmonisation 

2. Contact with the twin research community

 

*Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will be considered. In these circumstances the appointment will be made at Grade 5, spine point 30 with the title of Research Assistant. Upon confirmation of the award of the PhD, the job title will become Research Associate and the salary will increase to Grade 6. 

Further information

The post holder will need to be independent and self-driven.  

This post is subject to Disclosure and Barring Service and Occupational Health clearance. 

Twins, Long COVID