We are seeking a talented molecular epidemiologist who is familiar with the analysis and interpretation of genetics and other omics data to join our molecular epidemiology team. You will work within the department of epidemiology and biostatistics applying their expertise to molecular epidemiology to further develop our understanding of the molecular signals and pathways underlying the development of neurodegenerative diseases and their comorbidities.
This post is funded from the Uren Foundation and will be in close collaboration with the Dementia Research Centre at Imperial College London. In brief, we will apply advanced genetic epidemiology methodologies to identify shared and putatively causal genes for dementias and conditions with which they co-occur (e.g. cardiovascular conditions, other neurodegenerative conditions, mental health, inflammatory conditions). We will examine multi-omics correlates (transcriptomic, proteomic and metabolomic) and apply colocalization and mediation to examine potential causal pathways. Finally, we will investigate drug repurposing opportunities using molecular epidemiology approaches.
The post will include analysis of complex biomedical data and omics including genetic data (GWAS, polygenic risk scores) and metabolomics as well as other omics data (e.g. proteomics). The post is located in the Department of Epidemiology and Biostatistics, School of Public Health, which houses world-leading epidemiological resources including intense phenotyping of cardiometabolic traits and rich omics datasets including genomic, epigenomic, proteomic and metabolomic data. You will benefit from the diverse types of biomedical data, patient data, multi-omics data and other resources available within Imperial College London and its collaborative partners through Dementia Research Institute and the BHF Centre of Excellence. Coupled with state-of-the-art dedicated high-performance computers and a multi-petabyte storage system, this provides the capacity to develop powerful new approaches to the integration and analysis of large-scale, complex, multi-sources medical data and multi-variate data model construction and visualisation
You will collaborate closely with population and experimental scientists, including biochemists and chemometricians. Candidates will be interested in gaining/sharing knowledge and experience within and outside their domains, including in the areas of biostatistics, omics technologies, informatics, clinical and chemical science domains. You will be responsible for working with participating studies, harmonization of the clinical data across studies, bringing the clinical and omics data together, running omics analysis and interpreting the findings, and coordination with the biochemistry lab. You will be part of project teams to creatively share knowledge and experience including in the areas of biostatistics, omics technologies, informatics, clinical and chemical science domains.
We are looking to appoint individuals with a background in epidemiology, biostatistics or other related quantitative disciplines, with analytical and interpretative skills in epidemiology and omics data. You will collaborate closely with population and experimental scientists, including biochemists and chemometricians. Candidates will be interested in gaining/sharing knowledge and experience within and outside their domains. You will be part of project teams to creatively share knowledge and experience and should have knowledge and experience in biostatistics, epidemiology or another closely related discipline and strong skills with commonly used statistical tools and approaches.
The post is full time and fixed-term for 24 months and will be based at St Mary’s, Paddington, eventually moving to the White City campus as the department will eventually be based there.
For further information and advice on the application process contact Ms Eno Umoh ([email protected]); for a discussion on the work please contact Prof Ioanna Tzoulaki ([email protected]).
- JD Research Assistant - Associate in Molecular EPidemiology Uren DA.pdf