University of Geneva, Gravitational-Wave Science Center

Position ID:University of Geneva-Gravitational-Wave Science Center-PD4 [#23871]
Position Title: Postdoct position at the University of Zurich, on Cosmological simulations, galaxy formation, and super-massive black hole astrophysics
Position Type:Postdoctoral
Position Location:Zurich, Zurich 8057, Switzerland [map] sort by distance
Subject Areas: Astrophysics / Gravitational Waves, Astrophysics, Astrophysics and Gravitational Physics, Black holes, Computational Astrophysics, Numerical Astrophysics, Numerical Simulations, Theoretical Astrophysics
Appl Deadline:2023/01/15 11:59PMhelp popup (posted 2022/11/29, listed until 2023/02/01)
Position Description:    

Today is the last day you can apply for this position; no new applications will be accepted after 2023/02/01 11:59PM US Eastern Time.

We invite applications for a postdoctoral researcher to work on the simulation-based modelling of massive and intermediate mass black hole binaries from cosmological scales  to sub-pc scales prior to the onset of the GW-driven in-spiral phase. The goal is to develop a new multi-physics simulation framework by combining state-of-the-art N-Body + hydrodynamical/MHD simulations carried out at different scales with advanced machine learning techniques to design emulators of processes acting at a sub-grid level. The ultimate aim is to develop a new robust forecast model for event rates and distribution of properties of binaries in the LISA and Einstein Telescope bands. We seek candidates with deep expertise in cosmological  hydrodynamical simulations of galaxies and black holes, formation scenarios for massive and intermediate mass black holes,  and/or small scale simulations of disk-embedded  binaries and astrophysical disks.

The postdoc will be based at the Center for Theoretical Astrophysics and Cosmology of the Institute of Computational Science  (ICS) at the University of Zurich, and collaborate with several PhD students and postdocs working on advanced numerical and semi-numerical codes and models in the group of the ICS Director, Prof. Lucio Mayer. She/he will collaborate with another postdoctoral fellow to be hired  inside the GWlearn collaboration framework, who will be based at the Institute of Machine Learning at ETH Zurich (Prof. Thomas Hoffman's group). Members in Mayer's group develop and/or utilize several mult-purpose particle-based as well as grid-based parallel codes (PKDGRAV3, ChaNGa, GIZMO, DISCO), including the new Exascale SPH code  SPH-EXA, which is part of a swiss-wide collaboration with the National Supercomputing Center (CSCS). Access to top-notch supercomputing facilities is guaranteed with a long-term partnership with CSCS through dedicated node hours on both CPU and GPU platforms, such as the Alps/Eiger Cray supercomputer.

The initial appointment will be for three years, with the possibility of an extension for an additional year.

The review of applications will start immediately and will continue until 31/12/2022 or until the position is filled.

This position is part of GW-Learn, a multidisciplinary research program on Gravitational-Wave (GW) science, across Swiss universities. GW-Learn aims at developing techniques, theories, algorithms, and simulations that will allow for optimal knowledge acquisition from the next-generation GW observatories, such as the Einstein Telescope (ET) and the Laser Interferometer Space Antena (LISA). The successful candidates will have the opportunity to work with a team of world-leading experts in GW astrophysics, Machine Learning, GW data analysis, Cosmology, Fundamental Gravity, and  Experimental Physics, including Profs. Tassos Fragos, Michele Maggiore, Corinne Charbonnel, Antonio Riotto, and Steven Schramm from University of Geneva, Profs. Lucio Mayer and Philippe Jetzer from the University of Zurich, Profs. Thomas Hofmann and Domenico Giardini from ETH-Zurich, Dr. Elena Cuoco from the European Gravitational Observatory (EGO),  and Dr. Jonathan Gair from the Max-Planck Institute for Gravitational Physics (Albert Einstein Institute) 

Additional opportunities within GW-Learn can be found here:

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Further Info:
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