Postdoctoral Fellow : Cambridge, United Kingdom

Job Description

A Postdoctoral position in computational biology/genomics is available in the Statistical Genomics and Systems Genetics group (www.ebi.ac.uk/research/stegle) at the European Bioinformatics Institute (EMBL-EBI) located on the Wellcome Trust Genome Campus near Cambridge in the UK.

The group is using statics as a tool to analyse complex datasets, in particular in the context of multi-omics association genetics. This project will be part of a H2020 funded project “PanCanRisk”, tackling key computational challenges in modelling the genetic risk factors of cancer. In particular, we aim to derive new computational and statistical approaches to fully exploit large-scale pan-cancer datasets, allowing integrating data from multiple cancer entities and omics layers. 

You will be located in the Stegle group and collaborate with partners in the project to develop analytical strategies for tying together genetic associations with molecular traits such as gene expression levels (eQTLs) and epigenetic marks, integrating information on 3d chromatin interactions. The primary goal is to derive powerful approaches to fully harness the datasets that are being generated with large pan-cancer initiatives (PCAWG), thereby studying tissue-type specific effects of somatic and germline mutations.

EMBL-EBI is part of the European Molecular Biology Laboratory (EMBL). We are a world-leading bioinformatics centre providing biological data to the scientific community with expertise in data storage, analysis and representation. We provide a dynamic, international working environment and have close ties with both the University of Cambridge and the Wellcome Trust Sanger Institute.  EMBL-EBI staff enjoy many benefits including excellent sports facilities, a free shuttle bus to Cambridge and other nearby centres, an active sports and social club and an attractive working environment set in 55 acres of parkland.  
 

Qualifications and Experience

You will hold a doctoral degree or equivalent qualification in computer science, statistics, mathematics, physics, and/or engineering, or a degree in biological science with demonstrated experience in computational and statistical work.

Previous experience in developing and applying computational methods in the context of genomics analyses is expected. Expertise in analysis and integration of multiomics data, statistical genetics, statistical interpretation and analysis of next-generation sequencing datasets is beneficial, as is communicating results in scientific conferences and papers.

We especially seek candidates with prior experience in statistical aspects of genomics, including gene expression data analysis, GWAS and analysis of NGS data. A good foundation in, and previous usage of methods in any of the following fields is advantageous: statistics, machine learning, genetics, optimization and mathematical modeling. A background in molecular biology, or previous experience tackling biological questions is beneficial but not necessary.

Proficiency with a high-level programming language (e.g., C++, Java) and/or appropriate scripting languages, and statistical data analysis tools such as R, MATLAB or Python is required.

You will be able to demonstrate the ability to work independently and creatively. (S)he should have excellent communications skills and be able to articulate clearly the scientific and technical needs, set clear goals and work within an interdisciplinary setting, communicating with other partners within the H2020 project.

Additional Information

 EMBL is an inclusive, equal opportunity employer offering attractive conditions and benefits appropriate to an international research organisation. 

Please note that appointments on fixed term contracts can be renewed, depending on circumstances at the time of the review. 

We welcome applications from all nationalities. Visa information will be discussed in more depth with applicants selected for interview. 

Please note applications will close at 11pm (UK time) on the date listed above.