PhD position: modeling RNA-protein interactions and inferring post-transcriptional regulatory codes

November 12, 2009

Sponsored Links

Career Blog

The Wisconsin Idea Scholarship, University of Wisconsin–Madison

Online Distance Learning Courses for International Students

PhD position: modeling RNA-protein interactions and inferring post-transcriptional regulatory codes

In the recent years it became apparent that normal development
involves regulatory interactions of proteins and non-coding RNAs with
target mRNAs, whose lifetime and protein output is thereby
modulated. Over-expression of specific RNA-binding proteins as well as
of regulatory RNAs such as miRNAs have been associated with various
diseases, in particular with cancers. Developments in sequencing
technologies coupled with novel experimental protocols yield large
numbers of binding sites for various regulators. Analyses of such
binding sites, together with various types of physical measurements
(affinities of interactions, structure of regulator-target complexes,
etc.) should enable us to understand and subsequently predict with
high accuracy binding sites genome-wide and to study the extent and
structure of these regulatory networks.

The group of Mihaela Zavolan (Biozentrum Basel and Swiss Institute of
Bioinformatics) aims to understand the logic and function of
post-transcriptional regulation of gene expression during basic cell
function, development and cancer. For this purpose we generate,
analyze and computationally model large high-throughput biological
data sets. We currently seek a highly motivated PhD student with a
very strong quantitative background, interested to join our highly
dynamic research group in order to investigate the logic of RNA
binding protein – target interactions and the function of these
interactions in normal and pathological conditions.

Relevant references

Relative contribution of sequence and structure features to the mRNA
binding of Argonaute/EIF2C-miRNA complexes and the degradation of
miRNA targets. Hausser J, Landthaler M, Jaskiewicz L, Gaidatzis D,
Zavolan M. Genome Res. 2009 Sep 18. [Epub ahead of print]

Inference of miRNA targets using evolutionary conservation and pathway
analysis. Gaidatzis D, van Nimwegen E, Hausser J, Zavolan M. BMC
Bioinformatics. 2007 Mar 1;8:69.

Requirements

We are looking for candidates with a background computer science,
physics/biophysics, applied mathematics, computational biology or
bioinformatics, and a demonstrated ability to perform
research. Candidates should have experience in programming, preferably
in C/C++ and a scripting language like Perl or Python. Although a
formal training in molecular biology is not required the succesful
candidates will be expected to collaborate closely with experimental
colleagues and good communication skills are highly desirable.

Please submit your application letter, CV and the contact information
of two references before December 15, 2009 to:

Prof. Mihaela Zavolan
Biozentrum Universität Basel
SIB – Swiss Institute of Bioinformatics
Klingelbergstrasse 50-70
4056 Basel Switzerland
email: mihaela.zavolan-at-unibas.ch

Scholarship