PhD position in probability and Monte Carlo methods in neuroinformatics

The Department of Mathematics at KTH Royal Institute of Technology, in collaboration with the Swedish e-science Research Center (SeRC), invites applications for a PhD position in uncertainty quantification and stochastic numerical methods for modelling the brain. The successful candidate will pursue a PhD project at the intersection of probability theory, mathematical statistics and computational mathematics, with a focus on statistical inference in high-dimensional dynamical systems. The research questions are stemming from neuroscience and an area often referred to as neuroinformatics or systems biology. The project is part of SeRC's Brain-IT program, see https://e-science.se/people-and-research/mcps/mcp-brain-it/.

Monte Carlo methods have become essential tools for modelling and computational tasks in complex systems. The aim of the project is to develop robust and scalable methods for uncertainty quantification and sensitivity analysis of models related to the brain, with a focus on intracellular nerve cell models. More generally the aim is to construct and analyse Monte Carlo methods - e.g. approximate Bayesian computation, Hamiltonian Monte Carlo and stochastic numerical methods for processes on Riemannian manifolds - that are appropriate for models in neuroscience, including their theoretical properties (e.g. convergence, optimal parameters, scaling limits). An important aspect is the implementation of these methods in a reusable fashion, including a structured handling of models and data. 

The position is a time-limited, full-time, five year position starting August 2020 or at an agreed upon date. The position is fully funded for four years and will be extended to five years by assigning teaching duties. The position is financed by the Department of Mathematics and the Brain-IT MCP within SeRC. Supervisors will be Pierre Nyquist (mathematics), Olivia Eriksson and Andrei Kramer (computational sciences, SeRC). Alexandra Jauhiainen (Astra Zeneca and collaborator in the UQSA subproject of Brain-IT) will also be involved.

Within the Department of Mathematics at KTH, the successful candidate will be part of vibrant and diverse groups in Probability and Mathematical Statistics. There will also be strong interactions with the ``Brummer \& Partners MathDataLab'', a research lab in mathematics and applied mathematics, hosted at the Department of Mathematics, that aims at creating a hub for mathematical research in the analysis of complex data.  The candidate will also be part of the SciLifeLab (https://www.scilifelab.se/). 

Students interested in one or more fields related to the following are encouraged to apply: probability theory, statistics, Monte Carlo methods, uncertainty quantification, computational mathematics, stochastic analysis, machine learning, differential geometry, neuroinformatics. Ideally, applicants should have a sound training in probability theory (including stochastic processes and stochastic differential equations) or computational mathematics. Some programming experience is also necessary.

The official application period opens May 14 via KTH's recruitment system (https://www.kth.se/en/om/work-at-kth/lediga-jobb). Intersted students are encouraged to contact Pierre Nyquist as soon as possible for a informal conversation or an early application (must include the same material as the official application, see attached PDF); qualified candidates may then be asked to resubmit the same material via KTH Recruitment once the position opens there.

For more information and links to the application system (once open to submissions) see https://people.kth.se/~pierren/open.html.

Organisation: 
Job location: 
KTH
10044 Stockholm
Sweden
Contact and application information
Deadline: 
Thursday, May 28, 2020
Contact name: 
pnyquist
Contact email: 
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