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.
The application deadline is April 10. If you think you may be interested, you are welcome to contact Tom Nielsen (firstname.lastname@example.org) or Tom Matheson (email@example.com) with any questions.