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Two research positions are available to support and improve the Baysig platform, which forms the core of BayesHive. We are looking for two postdocs to work on a practical system for large-scale inference in scientific and clinical datasets using bayesian statistical models, embedded in a typed functional programming language and based on stochastic dynamical systems. In particular, we are looking to develop: * A typed hierarchical database that uses a Hindley-Milner-like typesystem (with records) to organise large, complex and heterogeneous data from a hospital. * Probabilistic inference over these complex datasets * Parallel Bayesian inference * Models for clinical datasets (for instance ECG) using dynamical systems. These positions are University-based research positions and there is scope for exploring designs for functional-probabilistic programming that are different from the current implementation of Baysig. One position emphasises the programming language research and the other focuses on the statistical modelling. [Particulars, Position 1](http://ig5.i-grasp.com/fe/tpl_UniversityOfLeicester01.asp?newms=jj&id=85616&aid=14178) [Particulars, Position 2](http://ig5.i-grasp.com/fe/tpl_UniversityOfLeicester01.asp?newms=jj&id=85615&aid=14178) The application deadline is April 10. If you think you may be interested, you are welcome to contact Tom Nielsen (tomn@openbrain.org) or Tom Matheson (tm75@le.ac.uk) with any questions.