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ALLSTAT  October 2013

ALLSTAT October 2013

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Subject:

JOB: Three Research Associate positions in Statistical Genetics / Bioinformatics / Computational Biology - Imperial College London

From:

Leonardo Bottolo <[log in to unmask]>

Reply-To:

Leonardo Bottolo <[log in to unmask]>

Date:

Wed, 2 Oct 2013 14:37:12 +0100

Content-Type:

text/plain

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Research Associate in Statistical Genetics (SM188-13)
Research Associate in Bioinformatics (SM189-13)
Research Associate in Computational Biology (SM229-13)
Imperial College London, School of Public Health / Department of
Genomics of Common Disease,
Salary range: 28,770  41,540 per annum
Closing date: 23 October 2013 (midnight BST)

Applications are invited for Postdoctoral Research Associate positions
in Statistical Genetics / Bioinformatics / Computational Biology to
join the research group of the Department of Genomics of Common
Disease, Imperial College London. These positions represent an
exciting opportunity for talented applicants to join a competitive
interdisciplinary team working on problems at the forefront of human
genomics.

The Department of Genomics of Common Disease is a world leader in
genomic research of common human diseases. As part of a major
expansion of our research activities, in collaboration with the
Department of Mathematics, we are reinforcing our computational
biology team. The successful candidate will harness statistical and
computational approaches to develop and apply integrative genomics
methods aimed at the identification of genomic and non-genomic
biomarkers, and their interactions, involved in phenotypic variation
in humans. They will integrate information from multiple data sources,
including genomic sequencing, structural variant, epigenetic and
transcriptomic multi-tissue data, and phenome data (quantitative and
end-point phenotypes, environmental variables, clinical parameters,
NMR and mass-spec metabolomics data), to build their interaction
networks and infer the underlying biological pathways. Close
interaction with the genomics laboratories within the Department will
allow further refinement and validation of the computational models.
Current projects aim to disentangle the genomic basis of a wide range
of end stage qualitative phenotypes including metabolic diseases,
cancer, ageing, and renal diseases, as well as quantitative phenotypes
measured in the healthy and diseased population.

Our studies include a variety of study designs, including genetic
isolates, in which individuals are related to each other through
multiple lines of descent. One of the aims of the computational
biology team will therefore be to extend novel and available methods
to allow data integration in related individuals.

These are opportunities for ambitious researchers with a strong
academic background in statistical genetics / bioinformatics /
computational biology / computer science and an interest in applying
their skills to lead the development of novel methods and
computational tools for genomic research.

Candidates should hold a PhD or equivalent in statistics /
bioinformatics / computational biology / computer science and have a
good publication track record, be highly motivated individuals,
demonstrate excellent communication skills, and have the ability to
work both independently and within a multidisciplinary team.

The position is full time and fixed term for 2 years and will be based
at the Hammersmith Hospital Campus, East Acton.

The post-holder will work under the supervision of Dr Mario Falchi and
closely with other academic members of the Department of Genomics of
Common Disease (including Professor Philippe Froguel, Dr Inga
Prokopenko, Dr Toby Andrew) and Dr Leonardo Bottolo from the
Department of Mathematics at Imperial College London.

For informal enquiries please contact Dr Mario Falchi
([log in to unmask]) or Mrs Pat Murphy
([log in to unmask]).

For further particulars, or to make an application, visit:
http://www3.imperial.ac.uk/employment

You may leave the list at any time by sending the command

SIGNOFF allstat

to [log in to unmask], leaving the subject line blank.

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