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
Particulars, Position 2
The application deadline is April 10. If you think you may be interested, you are welcome to contact Tom Nielsen ([email protected]) or Tom Matheson ([email protected]) with any questions.