Studentship in likelihood-free Bayesian inference and deep learning, Gothenburg

Are you looking for a PhD project in Bayesian inference?

Are you interested in the opportunities offered by deep neuronal
networks for AI?

A PhD student position is available at Dept. Mathematical Sciences at
Chalmers University in Gothenburg, on inference for models with
analytically “intractable” likelihoods, using approximate Bayesian
computation (ABC) powered by deep neuronal networks (DNN).

You will be part of an international collaboration to create new
methodology bridging between ABC and DNN for Bayesian inference in
stochastic modelling.
If you have an interest in inference for models based on stochastic
differential equations, that’s a plus.

Details on the project are at
https://www.chalmers.se/en/about-chalmers/Working-at-Chalmers/Vacancies/Pages/default.aspx?rmpage=job&rmjob=8281

The PhD student position is fully funded and is up to 5 years, in the
dynamic and international city of Gothenburg, the second largest city in
Sweden, https://www.goteborg.com/en/
As a PhD student in Mathematical Sciences you will have opportunities
for many inspiring conversations, a lot of autonomous work and some travel.

The position will be supervised by Assoc. Prof. Umberto Picchini.

The project is part of a joint call for 6 PhD positions distributed
across 6 projects. As an applicant, you will be considered for all of
the projects but it is important that you mention in the application
your specific research interests and indicate which of the projects you
are most interested in.

Apply by 6 March 2020 following in the instructions at
https://www.chalmers.se/en/about-chalmers/Working-at-Chalmers/Vacancies/Pages/default.aspx?rmpage=job&rmjob=8281

For informal enquiries, please get in touch at picchini@chalmers.se
Best regards
Umberto Picchini
Umberto Picchini picchini@chalmers.se
Associate Professor https://umbertopicchini.github.io/
Department of Mathematical Sciences Twitter: @uPicchini
Gothenburg University and Phone (office): +46 317 726 414
Chalmers University of Technology