Research Associate - Cheminformatics and Computer-Aided Drug Design Methods for the Selection of Anti-Alcoholism Agents SyBil-AA Project
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Research Associate - Cheminformatics and Computer-Aided Drug Design Methods for the Selection of Anti-Alcoholism Agents SyBil-AA Project

Applications are invited for a post-doctoral research associate to join the group of Dr Andreas Bender (http://www.ch.cam.ac.uk/group/bender/index) in the second half of 2017 for a period of 2 years. The project will utilize cheminformatics, bioinformatics and computer-aided drug design (CAD) methods for the selection of bioactive compounds with the desired polypharmacology profile against a range of central nervous system (CNS) targets. Compounds will be prospectively tested both in vitro and in vivo, with the aim to make major contributions towards the understanding as well as the therapy of alcohol addiction.

The position is part of a major EU project, SyBil-AA ("Systems Biology of Alcohol Addiction (SyBil-AA): Modelling and validating disease state networks in human and animal brains for understanding pathophysiology, predicting outcomes and improving therapy"), involving 11 universities, research centres and commercial partners. Further information about the project can be found at this location: http://sybil-aa.eu/.

The research associate will be based at the Centre for Molecular Informatics in the Department of Chemistry of the University of Cambridge (http://www.cam.ac.uk), which is home to about 40 scientists in the cheminformatics and bioinformatics fields. The project will be well-embedded into the current expertise available at the centre, and regular travel for consortium meetings within Europe will be required.

Applicants should have (or be about to obtain) a relevant PhD in the fields of bioinformatics, cheminformatics, scientific data analysis or related fields. Expertise in the areas of scientific programming, databases, and data mining packages (such as R, KNIME, scikit-learn, or similar) are essential for the post, as is a scientific understanding of chemical and biological information. Previous experience in the analysis of ligand-target bioactivity profiles (in silico target prediction, docking, proteochemometrics modelling, other forms of QSAR, etc.) would be highly advantageous, as would be knowledge about CNS drug discovery and the GPCR target family in particular.

Fixed-term: The funds for this post are available for 2 years in the first instance.

To apply online for this vacancy and to view further information about the role, please visit: http://www.jobs.cam.ac.uk/job/11255. This will take you to the role on the University’s Job Opportunities pages. There you will need

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