[Socbin] Opportunities in probabilistic modelling: post-doctoral fellowships in computational biology, Vienna

Dr. D. P. Kreil socbin08 at kreil.org
Fri Jan 11 22:17:48 CET 2008


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Boku University Vienna
Department of Biotechnology
WWTF Chair of Bioinformatics


Vacancies for

Post-doctoral research fellows in Computational Biology / Probabilistic Analysis

Join our fast growing team! We are a young group focussing on the challenge of extracting structured insight from high-throughput experiments (microarrays, proteomics, 
), taking a quantitative approach in the lab and applying probabilistic models in analysis. Our biological interests are varied, and include clinical applications as well as basic research, such as the investigation of non genetic sources of individuality in fruit-flies. While travel is not necessary, we have active collaborations with Cambridge, UK, and the U.S., and encourage exchange with our partners. Vienna is a thriving international city with a vibrant scientific environment and outstanding quality of life.

We are looking for skilled and enthusiastic researchers to join our team contributing to

 - the calibration and deconvolution of complex mixture signals in gene expression assays

 - the identification of molecular mechanisms of ageing in Drosopihla melanogaster

Improved methods will be developed for the quantification of gene expression exploiting thermodynamic sequence properties and probabilistic inference. The project equally requires an interest in mathematical modelling and the design and evaluation of appropriate microarray experiments. For this you need a proven track record of implementing and applying probabilistic models using Markov Chain Monte Carlo or variational methods. An understanding of thermodynamics and non-equilibrium effects may also be helpful. Work involves regular interactions with laboratory scientists and engineers. Address applications to David Kreil.

Our investigation of molecular determinants of ageing needs a dedicated data analysis expert. A particular goal is the implementation and application of probabilistic approaches for an analysis of microarray time-course experiments to reveal static and temporal patterns that are related to ageing processes. For this you need a proven track record in probabilistic machine learning or Bayesian statistics. Work involves regular interaction with biologists. Apply to Peter Sykacek.

Successful candidates will hold a PhD degree in a technical or scientific field and show proficiency  using R or MatLab / Octave. Experience with data analysis in a biomedical or life-science domain is a considerable advantage. Responsibilities include assisting in the planning of well-designed experiments and taking personal responsibility for the full subsequent data analysis process. An interest in collaborating with researchers from other domains and excellent communication skills are thus essential.

Positions are available immediately with an initial tenure of up to 3 years, and extensions possible. We look forward to receiving your application (cover letter, CV, publication list) by 15 Jan. 2008. Please arrange for 3 references to be sent to us directly. Late applications may be considered until the vacancies have been filled. Please feel free to contact us ( http://bioinf.boku.ac.at ).

Note that we also advertise all our vacancies online, see http://www.biotec.boku.ac.at/bijobs.html.


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