Postdoctoral Fellow (Computational Biology/Genomics)

Organization: 
European Bioinformatics Institute (EMBL-EBI)
Job Location: 
Wellcome Trust Genome Campus near Cambridge in the UK
Job Description: 

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

The group develops and applies new computational tools to study genotype to phenotype relationship from datasets generated in the context of the HipSci consortium (http://www.hipsci.org). The specific goals of this position are to devise new approaches for tying together genetic variation data, molecular traits, including RNA-Seq data, ChIP-Seq and proteomics with global phenotypes. Through statistical modeling and data analysis, we hope to understand how genomic variation impacts on cellular phenotypes, cell differentiation and disease.

The fellow will work between the Stegle group and the Birney Research group at EMBL-EBI and closely interact with the members of the HipSci consortium. This position offers the unique opportunity to develop integrated analysis approaches in the context of a cutting-edge genomics and stem cell initiative. We have close links to the University of Cambridge providing a strong statistics and machine-learning environment.

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.

Requirements: 

The successful applicant 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 computational methods and implementing them in software in a scientific context is expected. Expertise in analysis and integration of multiomics data, statistical interpretation and analysis of next-generation sequencing datasets is very 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, optimisation and dynamical systems. A background in 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.

The ideal applicant should have demonstrated 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 wet-lab and computational partners.

Contact Information: 

Please apply online through www.embl.org/jobs

About Our Organization: 

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