A 3.5 year EPSRC-funded studentship at Warwick Systems Biology Centre is
available from September 2011 to work on advanced Bayesian computational
methods for bioinformatics and systems biology.
The student will be part of a interdisciplinary research project to develop
advanced statistical theory and algorithms that will directly address current
challenges in scientific modeling in biology, astronomy and econometrics. This
research is a collaboration with experts in statistical machine learning (Prof.
Zoubin Ghahramani, Cambridge), statistics and econometrics (Dr. Jim Griffin,
Kent) and astronomy (Prof. Andrew Liddle, Sussex).
A variety of projects are possible, depending on the background and interests
of the student, and include:
o Applications of nonparametric Bayesian modeling to a number of
contemporary problems in computational biology, including:
- static and time-varying graphs, such as molecular structures
and dynamic regulatory networks
- data integration from multiple molecular phenotype platforms,
such as transcriptomics, proteomics, and metabolomics
o The development of new methods for Bayesian experimental design
o The construction of efficient algorithms for inference in
high-dimensional, highly-dependent structured data sets,
based on GPU computation
Warwick Systems Biology Centre is co-located with the MOAC (Molecular
Organisation and Assembly in Cells) PhD Programme and offers a thriving
research and postgraduate training environment at the interface of the life
sciences and the mathematical and physical sciences.
Candidates should have a good first degree in a relevant quantitative field
such as applied mathematics, statistics, theoretical physics, theoretical
chemistry or computer science and a strong interest in molecular biology. Good
programming skills in a high level language such as Matlab, R or C/C++ would be
advantageous.
For informal discussions, and applications, please contact Prof. David Wild
([log in to unmask]) in the first instance.
Applicants should include a full CV and accompanying letter outlining their
interests and any previous work.
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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