Postdoc in Computational Fluid Dynamics

Swiss Federal Institute for Forest, Snow and Landscape Research WSL

The Swiss Federal Institute for Forest, Snow and Landscape Research WSL is part of the ETH Domain. Approximately 600 people work on the sustainable use and protection of the environment and on the handling of natural hazards.

The Environmental Fluid Dynamics group of Dr. Markus Holzner at WSL (ETH Domain) is looking for a Postdoctoral fellow within the PHRT (Personalized Health and Related Technologies) research project "Deep Flow Imaging for Guiding Cerebrovascular Interventions" with a start on
**April 1st, 2023**, for the duration of
**1 year** (with possibility for extension).

PostDoc in computational fluid dynamics / biomedical flow research 80-100% (f/m/d)

You will work in an interdisciplinary team across the ETH Domain connecting experts in cardiovascular imaging (Prof. Sebastian Kozerke, ETHZ), machine learning (Prof. Ender Konukoglu, ETHZ) and fluid dynamics (Dr. Markus Holzner) with medical partners at the University Hospital Zurich (Prof. Dr. med. Tristan Van Doormal, Dr. med. Kulcsar Zolt) and EPFL (Prof. M. Unser). You will be based in Dr. Markus Holzner’s Research Group, with offices at WSL Birmensdorf and ETH Zurich.

You will conduct Computational Fluid Dynamics (CFD) simulations of blood flow in aneurysmal cerebral arteries and lumped parameter modelling of arteriovenous malformations linking cardiovascular imaging, machine learning and fluid dynamic modelling. Your tasks include the generation of anatomic models from patient angiograms, mesh generation for CFD, performing blood flow simulations using CFD software and lumped parameter modelling using in-house codes. Based on this output, you will generate synthesized 3D/4D/5D MRI data with target spatiotemporal resolution and signal-to-noise ratio that will serve as a ground truth for deep neural network training. You will address key questions such as: How do modulations in the in/outlet conditions affect flow patterns? Does full flow field inference allow for improved classification relative to CFD simulations with anatomical input alone or approximation using a few slices? You will present results at international conferences and publish in scientific journals.

You have a PhD in engineering, physics or a similar field, with extensive experience in computational fluid dynamics. A basic background in biomedical engineering is an asset. You have an excellent background in programming and handling large data. You are very motivated and strive to work independently and goal-oriented. You have excellent communication skills and you like working in a team.
- Zürcherstrasse 111, CH-8903 Birmensdorf