Postdoc Position in Machine Learning at FU Berlin

Postdoc Position in Machine Learning and the sequence-dependent statistical mechanics of DNA to be held at the Freie University Berlin.

In the context of a collaboration between Professors Ch. Schuette and J.H. Maddocks supported by an Einstein Foundation Berlin Visiting fellowship

there is a postdoc position available to work on establishing connexions between consensus protein binding site sequences and the physical characteristics of the associated DNA fragment. More specifically the objective of the project is to use the coarse-grain cgDNA model to generate Gaussian approximations to the localised equilibrium distributions of the DNA configuration in sliding windows along genomes, with machine learning techniques used to characterise the significant common features of the cgDNA Gaussians at already known binding sites for various proteins as identified in bioinformatics data bases. The ideal candidate would hold a computationally oriented PhD with a background in one or more of machine learning, bioinformatics and mathematical modelling.

The position is available as soon as 1.9.2019 with the ideal start date being no later than 1.1.2020. In the first instance the contract will be for 12 months, with the possibility of renewal on mutual consent at least for a further year. Applications containing a CV and publication list, a motivational statement, and names and email addresses of three possible referees should be sent to

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