Position Description

Postdoc: Multiscale thermodynamics, superfluids, and machine learning

This postdoc position is about geometric reduction techniques in non-equilibrium thermodynamics and statistical physics, and about applications in superfluids. Reduction techniques are important because they find low-dimensional patterns in otherwise exceedingly complex behavior. The reduction techniques are then applied to models and simulations of superfluid helium-4, where many theoretical problems remain open (like the energy of a compressible superfluid, quantum vortices, etc). We focus on geometric technique s (Hamiltonian mechanics, contact geometry, etc), so that the results are independent of representation.

• Numerics: solving hyperbolic partial differential equations for superfluids, smoothed particle hydrodynamics, or Hamilton-Jacobi equations.
• Multiscale non-equilibrium thermodynamics and statistical physics.
• Machine learning for recognition of patterns in statistical physics or in data describing superfluid helium.

• Condition: Ph.D. degree obtained after Dec 31, 2014.
• The salary will be CZK 52 K/month (plus the social and health insurance, can vary upon agreement).
• The position is located in Prague, Czech Republic (Mathematical Institute, Faculty of Mathematics and Physics, Charles University).
• The position is available from July 2023 (or later) to December 2025 (may be shorter if needed).
• Contact: Michal Pavelka, pavelka@karlin.mff.cuni.cz, www.karlin.mff.cuni.cz/~pavelka