PhD studentship in machine learning and protein feature prediction

[Mikael Bodn]

Applications are invited for a fully funded PhD studentship in the area of 
machine learning methods for protein feature prediction. The project is 
supported by the Swedish Research School in Genomics and Bioinformatics.

PROJECT DESCRIPTION AND AIM
The difficulty of in vivo experimentation often hinders production of large 
biological data sets. Inadequately sized data sets do not easily lend 
themselves to statistically sound and proper data analysis. Informed choices of 
representation and algorithm are required for data analysis tools to produce 
reliable results.

This project aims to provide the groundwork for computational analyses of 
protein structure and function that use the amino acid sequence information, 
through a thorough study that pinpoints the strengths and weaknesses of 
different representations and algorithms. The main goal of the research is to 
answer two questions: What is, both generally and specifically, a good 
representation of the amino acid sequence when one uses it to predict protein 
function? What is a good (efficient, robust, and trustable) algorithm to use 
for this task?

We foresee one outcome of the project to be guidelines for what biological 
questions are reasonable to ask given the amount of available data (or, 
conversely, how much data is required to answer specific biological questions) 
and what are good representations and algorithms for answering these questions. 
The project will make use of real data as gathered in collaborating projects to 
re-evaluate theoretical findings, and to contribute to the understanding of the 
biological phenomena even if only sparse data sets are available.

COMPETENCE
The successful candidate should have an MSc grade (or about to get one) or 
equivalent in computer science, statistics, mathematics or other related area 
with knowledge and interest in machine learning, neural networks and 
bioinformatics. Programming skills (e.g. MATLAB and Java) are desired.

CONTACT INFORMATION
Dr. Thorsteinn Rögnvaldsson, denni at ide.hh.se
Dr. Mikael Bodén, mikael.boden at ide.hh.se
Halmstad University
School of Information Science, Computer- and Electrical Engineering
Halmstad, Sweden.

APPLICATION
Closing date for applications June 28, 2002.
Further details are available from http://www.cmb.gu.se/research_school/.

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Dr. Mikael Bodén, http://www.hh.se/staff/mibo
School of Information Science, Computer and Electrical Engineering
Halmstad University, PO Box 823, S-30118 Halmstad, Sweden
Tel +46 (0)35 167473, Fax +46 (0)35 120348