The Computational Science and Engineering Lab (CSElab) at ETH Zürich is looking for a postdoc working in high-performance computing for uncertainty quantification, and optimization. The position is part of a multinational EU funded project on Bayesian uncertainty quantification (BUQ) on multi-scale computational models.

The research of the CSElab at ETH Zürich, headed by Prof. Dr. Petros Koumoutsakos, focuses on the development of high-performance computational tools for the study of complex scientific and engineering problems. Our main research areas are: Bayesian inference of parameters and uncertainty quantification of large scale computational models, machine learning algorithms for the prediction and control of complex dynamical systems, multi-scale modeling involving molecular dynamics, particle methods and macro-scale differential equation models.

This position is part of the project Data Driven Computational Mechanics at Exascale (DCoMEX), funded by Horizon 2020. This is a joint project with the National Technical University of Athens (NTUA), the University of Cyprus (UC) and the Technical University of Munich (TUM).

The project aims to provide advances to the field of computational mechanics by developing novel numerical methods enhanced by artificial intelligence algorithms that are deployed with scalable software to exascale computing architectures. Our methods fuse machine learning with efficient numerical methods and incorporate experimental data at multiple levels of fidelity to quantify model uncertainties. Efficient deployment of these methods in exascale computing architectures will provide scientists and engineers with unprecedented capabilities for predictive simulations of mechanical systems in applications ranging from bioengineering to manufacturing. The methodology will be demonstrated in two case studies:

• patient-specific optimisation of cancer immunotherapy treatment, and
• design of advanced composite materials and structures at multiple scales.

We offer you a full-time position, starting upon agreement with the earliest starting of 1 April 2022. You will work in an interdisciplinary team of researchers with in-depth experience in high-performance computing, BUQ, statistical modeling, ML, sampling and optimization algorithms.

You will work within a highly interdisciplinary project, which considers all aspects of the optimal planning, operation and assessment of the CCUS infrastructures. Your focus will be on life cycle assessment of pioneering and future CCUS supply chains. More specifically, you will participate in:

1. developing cutting-edge optimization and assessment algorithms to maximize the sustainability of CCUS infrastructures, while minimizing their costs and accounting for reliability;
2. characterizing and accounting for the uncertainty associated with the future evolution of CCUS infrastructures;
3. identifying and overcoming technical barriers for the deployment of large-scale CCUS infrastructures.

To this end, you will have access to state-of-the-art computational capabilities, and you will be in contact with experts worldwide.

We are looking for a proactive and motivated candidate who meets the requirements for a postdoc at ETH Zurich and has a university degree in Computational Science, Computer Science, Applied Mathematics, Engineering or Physics with a doctorate from a recognized University. You should have experience in computational methods, software development. and in super computing.

You will work in a dynamic environment with other doctoral students and postdocs. The ability to work independently and excellent communication skills in English (both written and spoken) completes your profile.