Stochastic and deterministic methods for high dimensional problems in molecular biology.
Intrinsic noise in biochemical networks can have a large impact on the behavior of biological cells. An example is the regulation of the transcription of genes to mRNA where the genes are present in one or two copies and the number of mRNA molecules is small. The facts that the copy number of each molecule is small and that there is a probability that a chemical reaction will occur when two molecules meet make a discrete, stochastic description of the system necessary.
The master equation is a differential-difference equation for the time evolution of the probability density for a system to be in a particular state at a given time. The system can come from molecular biology, where the states correspond to the number of molecules of different chemical species, from population dynamics, where the states correspond to the number of copies of different animals, or from epidemiology, where the states correspond to the number of infected, sick and healthy people.
The solution of the master equation is of interest for problems with many different species with variation in space giving rise to problems with very high dimension. Only stochastic Monte Carlo methods are available for computer simulation of such problems but they have disadvantages such as slow convergence. The purpose of this project is to develop deterministic and hybrid computational algorithms for the master equation in high dimensions and apply them to problems in molecular biology. We collaborate with the Elf and Ehrenberg groups at the Department of Cell and Molecular Biology at Uppsala University. Examples of topics of interest are: methods for problems with variation in space, coupling of methods suitable for different scales, adaptive methods, problems with a time delay. Our homepage is http://www.it.uu.se/research/group/ndim/molbio
The successful candidate should have a master of science in science or engineering. Good knowledge in applied mathematics, scientific computing, statistics, and programming is required. Good skills in oral and written English are necessary.
The PhD position is for a maximum of five years and includes departmental duties at a level of at most 20% (typically teaching). Further information: http://www.teknat.uu.se and http://www.it.uu.se.
The department is striving to achieve a more equal gender balance and female candidates are particularly invited to apply.
Applications should include a brief description of research interest and past experience, a CV, copies of exams, degrees and grades, a copy of your Master thesis (or a draft thereof) and other relevant documents. The candidates are encouraged to provide letter(s) of recommendation and contact information to reference persons.
For more information, please contact: Prof. Per Lötstedt, per.lotstedt@it.uu.se, tel: +46-18-4712972. Union representatives are: Anders Grundström, SACO-rådet, tel +46 18-471 5380, Carin Söderhäll, OFR-S/ST, tel +46 18-471 1996, Stefan Djurström, SEKO, tel +46 18-471 3315.
The application should be sent to: Registrator, UFV-PA 2008/724, Uppsala universitet, Box 256, 751 05 Uppsala, Sweden ; fax +46-(0)18-471 2000 or e-mail: registrator@uu.se no later than April 30, 2008. An application by fax or e-mail must be followed by a letter containing the original documents, at the latest a week after application deadline.
http://www.personalavd.uu.se/ledigaplatser/724dorand_eng.html
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