PhD position to study Protein Function Analysis/ Discovery at Stockholm Univ, Sweden

The research projects at the Department of Biochemistry and Biophysics cover a number of areas of high international interest, such as molecular studies on photosynthesis, mitochondria: biogenesis, structure and function, biochemical toxicology, lipid biosynthesis and function, protein structure, folding and trafficking, membrane protein topology and assembly, peptide-membrane interactions, bioinformatics, and biological nitrogen fixation. Research at the department involves plants, mammals, yeast, cyanobacteria and photosynthetic bacteria. The department is well equipped and within the projects modern gene technology and computer modelling are used as well as other biochemical, biophysical and physiological methods.

For more information about the department, see www.dbb.su.se.

Project title: Protein Function Analysis and Discovery

Project description

We are using machine learning and modelling techniques to infer protein function from protein sequence, protein evolution, or protein interactions. The goal is to build a map of all proteins with details on how they interact with each other and other molecules. A protein’s biochemical function and its context with interaction partners are key to undertanding its biological function. This map, or functional network, is explored to discover the function of previously uncharacterised proteins.

The methods include Bayesian Networks, Support Vector Machines, hidden Markov models, and own developed models. In this project, heterogeneous data sources are combined to predict functional coupling between proteins in order to build networks that model pathways and interaction cascades. These data sources include e.g. co-expression, co-evolution, protein interactions, and various sequence-based properties. A very important type of information is domain-domain interaction, which will be investigated by several approaches.

The project involves programming, data analysis, benchmarking, and modelling, but also application of the developed methods to genes of particular interest in order to discover new protein functions. See http://FunCoup.sbc.su.se and http://InParanoid.sbc.su.se

The successful candidate should have an M.Sc. in bioinformatics or related field, and knowledge of molecular biology. Alternatively, an M.Sc. in molecular biology or related field and at least 1 year of practical experience in bioinformatics research. Familiarity with sequence analysis techniques is essential, as well as a high level of motivation. Computer programming, UNIX skills, and knowledge of biological database systems are necessary merits.

Requirements
To be accepted as a PhD student, credits corresponding to four years of full-time studies at the undergraduate level are required, including credits corresponding to at least two years of fulltime studies in chemistry, life sciences or physics, depending on the program. The credits should include courses at the advanced level (second cycle) corresponding to one year and of these one semester should be a degree thesis. In order to facilitate the evaluation of merits and suitability for the PhD studies the curriculum vitae (CV) should contain information about the extent and focus of the academic studies. The quantity (as part of an academic year) and the quality mark of courses in chemistry and physics are of particular interest. Please state titles of undergraduate theses and project works.

Criteria for selection
The selection among applicants will be based on the judgement of their capacity to successfully complete the PhD program. In practical terms, this means that the study merits will be the main selection criterion. The local study merits, such as passed advanced courses or project work at the department, will be given a relatively high weight. Equal opportunity aspects between men and women will be given a certain weight, as well as willingness and ability of candidates to participate in undergraduate teaching.

Terms of employment
The selection among applicants will be based on the judgement of their capacity to successfully complete the PhD program. In practical terms, this means that the study merits will be the main selection criterion. The local study merits, such as passed advanced courses or project work at the department, will be given a relatively high weight. Equal opportunity aspects between men and women will be given a certain weight, as well as willingness and ability of candidates to participate in undergraduate teaching.

More information
More details about the project can be requested from project leader Erik Sonnhammer, e-mail Erik.Sonnhammer@sbc.su.se or Homepage: http://sonnhammer.sbc.su.se.

General information about the PhD training program may be requested from Astrid Gräslund, head of department (prefekt), telephone +46-(0)8-16 2450, e-mail astrid@dbb.su.se.

Union representatives are Bo Ekengren (SACO), Lisbeth Häggberg (Fackförbundet ST), telephone +46-(0)8-16 2000 (switch board), and Gunnar Stenberg (SEKO), telephone +46-(0)70-316 43 41.

Applications
The application should contain a letter of intent (one to two pages that explain why you are interested in working on this project, why you are interested in studying for a PhD, what you hope to accomplish during your PhD studies, and what skills you can bring to this project), curriculum vitae, copies of degree certificates and transcripts of academic records, a list of two persons who may act as referees (with telephone numbers and e-mail addresses), and one copy of your undergraduate thesis and articles, if any.

The applicant may apply for more than one position, but in that case, a complete set of documents is required for each position.

Completed applications, labelled with the reference number
SU DBB 18-10, should be received no later than November 20, 2010, by regular mail to:
Department of Biochemistry and Biophysics
c/o Haidi Astlind
Stockholm University
Svante Arrhenius v. 16
SE-106 91 STOCKHOLM
SWEDEN

or by e-mail to: haidi@dbb.su.se.

Tags: Bayesian Networks, Biochemistry, Bioinformatics, Biophysics, co-evolution, co-expression, cyanobacteria, Hidden Markov models, lipid biosynthesis, mammals, membrane proteins, PhD position biochemistry, protein evolution, Protein Function Analysis, Protein Interactions, protein sequence, protein structure, Stockholm Univ Sweden, Support Vector Machines, transmembrane ion transport, yeast

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