Research Associate, Department of Twin Research, School of Life Course Sciences
Research Associate, Department of Twin Research, School of Life Course Sciences
Job ID: 020404
Salary: £38,304 - £41,517 per annum, including London Weighting Allowance
Closing date: 06-May-2021
Business unit: Faculty of Life Sciences & Medicine
Department: Twin Research & Genetic Epidemiology
Contact details: Dr Cristina Menni, email@example.com
St. Thomas' Campus Research
We are seeking a highly motivated and skilled Post-doc to explore the relationships between gut microbes, serum and stool metabolites, glycosylated proteind and cardiometabolic outcomes.
Metabolites generated by gut microbes appear to be important causative factors of cardiometabolic diseases. Taking advantage of the richly phenotyped and genotyped TwinsUK cohort, coupled with newly generated interactive postprandial response (PREDICT) data, the candidate will run the largest GWAS of microbial metabolites to date in over 4000 twins and investigate links between faecal, serum metabolites and the metagenome producing a rich database of pathways and networks. The causative links between specific bacterial metabolites, cardiometabolic outcomes and pro-inflammatory glycans will be further investigated using a Mendelian Randomisation approach. Our study will identify causative links between microbes, glycans and cardiometabolic outcomes that will enable the design of optimal personalized dietary interventions to improve cardiometabolic health targeting the metabolites produced by gut bacteria.
All omics and phenotypic data needed to answer the above questions have already been generated as part of an awarded grant.
The successful candidate should have a solid background in bio-informatics, statistics, and epidemiology allowing them to analyse and interpret large data sets. In addition, the candidate should already have an excellent track record in writing, analysing and publishing research articles, as well as experience in interpreting microbiome and metabolomics data. They should be hard working, flexible and able to work in a multi-disciplinary team.
This post will be offered on a fixed term contract until November 2022.
This is a full time post.
- To run the largest GWAS of microbial metabolites; investigate links between faecal metabolites and the metagenome; and produce a rich database of pathways and networks.
- To identify the causative links between specific bacterial metabolites and arterial stiffness, and atherosclerotic plaque and pro-inflammatory glycans using an MR approach.
- To identify the contribution of the microbiome that is via protein glycosylation and to validate any findings using data from a high fat meal challenge.
- To assist with the analysis of quantitative omics data on twin and family data collected in the department.
- To employ appropriate genetic epidemiological methods and statistical techniques to the twin and family data.
- To liaise closely with the genetic, glycan and metabolomic analysis teams in exploring and developing the theoretical aspects of microbiome analysis, including the use of publicly available data sets to do this.
- To assist with the writing of publications for appropriate scientific journals and to present research findings at scientific meetings.
- Participate in all project meetings, including symposia and workshop.
- Participate in and contribute to the development and implementation of research programmes relevant to the work undertaken within the department.
- Contribute to the integration and collaboration of research project with other branches of the department and with external collaborators.
- Any other duties as agreed with the supervisor.
Communication & networking
- To collaborate with other specialised centres of excellence to achieve the highest standard of research and publications.
- To assist with teaching of staff and students in methods of metabolomics and microbiome analysis.
- Prepare papers for steering group as well as manuscripts, abstracts and grant applications.
- Write up results of your own research
- Liaise with internal and external research colleagues and support staff on research matters
- Make internal and external contacts to develop knowledge and understanding and form relationships for future collaboration
- Communicate material of a specialist or highly technical nature
- Decision making, planning & problem solving
- 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
- Make use of standard research techniques and methods
- Deal with problems which may affect the achievement of research objectives and deadlines
- Contribute to collaborative decisions making affecting the work of the team
- Identify areas for research, develop new research methods and extend the research portfolio
- Service delivery
- Provide answers to specialist queries within the area of statistical analysis within microbiome and twin research, providing detailed information and a range of solutions
- Deal with internal and external collaborators
- 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 microbiome analyses epidemiology, statistics, metabolomics, and computational biology
- To identify areas where further research may be needed
- Analyse and interpret the results of research undertaken and draw conclusions on the outcome
- Assist in the writing of grant application for future research undertaken within the department
- Team work, teaching & learning support
- Actively participate as a member of the metabolomics, microbiome and omics statistical analysis team
- Collaborate with academic colleagues on areas of shared research interest
- Attend and contribute to relevant meetings
- To assist with the teaching of staff and students in computational methods and assist with metabolomics, microbiome and genetic analysis techniques
- Be involved in the assessment of student knowledge and supervision of projects
- Assist in the development of student research skills
- 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
- Show consideration to others at all times
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
- PhD awarded in bio-informatics, statistics, epidemiology, system biology, mathematical science or other related quantitative discipline
- Excellent programming skills that include knowledge of R, other programming languages (python/perl/C), and use of statistical packages
- Excellent computational skills and experience with high performance computing cluster
- Proficient with large-scale datasets and analysis using the appropriate statistical methods from basic to advanced
- Experience with the implementation of software for computationally intensive analyses
- Ability to communicate effectively at all levels in a complex multi-disciplinary environment
- Ability to produce concise verbal and written reports
- Experience analysing big data sets
- Experience with the analysis of metabolomics or gut microbiome data
- Ability to work as part of a multidisciplinary team
- Ability to work on own initiative and meet competing and demanding deadlines
- Highly self-motivated and hard working
- Contacts with the local bioinformatics and statistical community
- Experience with twin studies
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.