Location: New York, USA
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job offers
Location: Barcelona, Spain
Applications Deadline: 15/07/2009
contact: rrhh [at] crg [dot] es
Applications Deadline: 15/07/2009
contact: rrhh [at] crg [dot] es
Job Description: Two postdoc positions are available to work with PI Joanna Masel at the University of Arizona in Tucson.
The Masel group\'s main research interests are in evolvability, gene networks, canalization, and evolutionary capacitance, using a mixture of analytical theory, bioinformatic and simulation approaches. Both positions are renewable over multiple years, and are available immediately.
One position will be to study the properties of cryptic genetic variation and evolvability via evolutionary capacitance using theoretical population genetics and/or bioinformatic approaches. Ph.D. with a strong quantitative background and computational and/or modeling experience is required. A background in evolutionary theory is strongly preferred. Some interest in the molecular biology of transcription, translation, protein folding and the errors in each of these processes is an advantage.
The second position involves completing the implementation of a computational model of transcriptional networks that is both realistic enough to be related to yeast data and simple enough for evolution to be rapidly simulated. The model will then be used to study a range of questions, including network topology and the evolution of robustness/canalization to mutation, to the environment, and to the stochasticity associated with small numbers of molecules in cells. This project is a collaboration with Mark Siegal (www.nyu.edu/fas/dept/biology/faculty/siegal) at NYU. Ph.D. with scientific programming experience is required. Experience in evolutionary biology, genomics, systems biology, mathematical modeling and/or the biology of transcription factors and their binding sites is preferred.
The Masel group\'s main research interests are in evolvability, gene networks, canalization, and evolutionary capacitance, using a mixture of analytical theory, bioinformatic and simulation approaches. Both positions are renewable over multiple years, and are available immediately.
One position will be to study the properties of cryptic genetic variation and evolvability via evolutionary capacitance using theoretical population genetics and/or bioinformatic approaches. Ph.D. with a strong quantitative background and computational and/or modeling experience is required. A background in evolutionary theory is strongly preferred. Some interest in the molecular biology of transcription, translation, protein folding and the errors in each of these processes is an advantage.
The second position involves completing the implementation of a computational model of transcriptional networks that is both realistic enough to be related to yeast data and simple enough for evolution to be rapidly simulated. The model will then be used to study a range of questions, including network topology and the evolution of robustness/canalization to mutation, to the environment, and to the stochasticity associated with small numbers of molecules in cells. This project is a collaboration with Mark Siegal (www.nyu.edu/fas/dept/biology/faculty/siegal) at NYU. Ph.D. with scientific programming experience is required. Experience in evolutionary biology, genomics, systems biology, mathematical modeling and/or the biology of transcription factors and their binding sites is preferred.
Job Description: Offering a One-year Post-Doctoral Fellowship (Assegno di Ricerca), at the University of Padova. The position is linked to the project “A BIOINFORMATIC AND SYSTEMS BIOLOGY APPROACH TO THE STUDY OF GENOME EXPRESSION DURING MYELOID DIFFERENTIATION”. The scientific activity will be carried out under the supervision of Dr. Stefania Bortoluzzi, at the Department of Biology. The official selection will be open in July 2009 (starting date: September 1, 2009) The fellow will be involved in all the parts of the scientific project, including data retrieval, integration, analysis and software development. Thus he/she must have a good background in functional genomics and bioinformatics, with particular regard to the expression data field. Programming skills will also constitute a preferential quality.
