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英国欧洲生物信息学研究所招收计算生物学博士后

2014年04月29日
来源:知识人整理
摘要:

Postdoctoral Fellow : Cambridge, United Kingdom

 

Job Description

 

A Postdoctoral position in computational biology 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 goal of the research group is to devise computational and statistical approaches to unravel the interplay of genotype, cellular factors and external influences and their implications for phenotype. We combine statistics with mechanistic modelling concepts to tie together genetic variation data, molecular profiling information and organismal phenotypes. Current research directions include statistical method development for genome-wide association studies, methods to dissect the genetics of molecular traits and causal modelling to predict functional targets for molecular intervention. Methodological research aims are embedded in close collaborations with experimental partners, providing ample opportunities to apply innovative methods to address pertinent biological questions.

 

The candidate will work on developing statistical and machine learning methods for analysing and integrating high-throughput data. The initial goal will be to predict causal molecular networks between genotype and downstream phenotypes, integrating genetic variation data, molecular phenotypes and organ-level phenotypes. We aim to validate these methods using high-throughput functional genomics assays and are particular interested in applications to the context of the Human Induced Pluripotent Stem Cell Initiative we are part of (http://www.hipsci.org). The fellow will have opportunities to interact with colleges in statistics in Cambridge and collaborate with experimental groups on the Genome Campus and EMBL.

 

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

 

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