[SocBiN] PhD Studentship in Statistical Machine Learning and Computational Systems Biology (Helsinki, Finland)

[Antti Honkela]

(Apologies for multiple postings.)

PhD studentship in developing novel probabilistic modelling and
statistical inference methodology and applying these methods to
problems in computational systems biology

Helsinki Institute for Information Technology HIIT, Department
of Computer Science, University of Helsinki

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The Helsinki Institute for Information Technology (HIIT) and the
Department of Computer Science at the University of Helsinki are
looking for a skilled
   DOCTORAL STUDENT.

The Department of Computer Science is the leading unit for computer
science research and education in Finland. The focus areas of research
and teaching at the department are (1) algorithms and machine
learning, (2) networking and services, and (3) software systems. Three
Finnish Academy-funded centres of excellence operate at the
department, and it works in close collaboration with the Helsinki
Institute of Information Technology. The department is one of ten
national centres of excellence in university education. The department
employs some 170 persons, and its total budget is 11 Million
Euros. The department has an outstanding research infrastructure,
including a 1920-core computing cluster

The doctoral student will develop novel probabilistic modelling and
statistical inference methodology incorporating structured prior
information from mechanistic models and apply these methods to
problems in computational systems biology. The aim of the project is
to develop hierarchical Gaussian process models for modelling gene
expression and regulation in complex experiments, such as with
evolutionarily related specimen. The work will take place in the group
of Dr Antti Honkela but it will involve collaboration with
experimental biologists. The project will build upon recent experience
in application of Gaussian process models on modelling gene regulation
by Dr Honkela and collaborators (Honkela et al., PNAS 2010; Titsias et
al., BMC Systems Biology 2012).

A successful applicant must have a MSc degree in computer science,
electrical engineering, mathematics, physics, or a related field. A
strong mathematical background and an interest in Bayesian modelling
and/or machine learning are necessary. An interest in computational
biology is essential but no prior experience is necessary.

The application deadline is 21 June 2012.
For more details and application instructions, see
   http://www.helsinki.fi/recruitment/index.html?id=56832


Antti Honkela

-- 
Antti Honkela
antti.honkela at hiit.fi   -   http://www.hiit.fi/u/ahonkela/