PhD Student

Digital twin of miniaturized mineral precipitation experiments based on machine learning and multiscale modelling

Your tasks

  • Develop a digital twin for miniaturized counter-diffusion experiments with simultaneous dissolution precipitation of minerals in different types of porous media. Advanced numerical simulations and machine learning will be combined with cuting edge experiments, which will be conducted by an experienced team within the same project, at the Swiss Light Source SLS and other large scale facilities of PSI
  • Within the existing framework of in-house scientific codes and machine learning tools CPU/GPU, adapt state-of-the-art pore scale reactive transport numerical models (lattice Boltzmann method) and accelerate geochemical calculations using machine learning and surrogate models
  • Apply diffraction pattern recognition for the classification of reaction products, apply 2D/3D reactive transport numerical simulations, design of experimental runs with optimized experimental conditions
  • Publication of results in journals and conferences

Your profile

  • You are able to work independently in a collaborative and interdisciplinary research team
  • Msc in Engineering/ Computer Science / Natural Sciences / Environmental Sciences
  • Experience in machine learning (e.g. classification / neural networks) and/or numerical simulations, fluid dynamics (ideally with lattice Boltzmann method) is beneficial
  • Experience with coddes for CPUs and/or GPU's (C/Cuda/Python)
  • Fluency in English is required (spoken and written)

We offer

Our institution is based on an interdisciplinary, innovative and dynamic collaboration. You will profit from a systematic training on the job, in addition to personal development possibilities and our pronounced vocational training culture. If you wish to optimally combine work and family life or other personal interests, we are able to support you with our modern employment conditions and the on-site infrastructure.

This project is part of the CROSS-interdisciplinary project "In-situ 4D micro X-Ray chemical imaging and a digital twin of miniaturized counter-diffusion experiments" and includes extensive interactions with the Laboratory for Scientific Computing and Modelling, the Photon Science Division and the Research with Neutrons and Muons Divisions of PSI. You will be registered as a PhD Student at University of Bern, Switzerland ( under the supervision of Prof Dr Sergey Churakov.

For further information, please contact Dr Nikolaos Prasianakis, phone +41 56 310 24 15 or Email

Please submit your application online by 30 May 2021 (including addresses of referees) for the position as a PhD Student (index no. 4403-00).

Paul Scherrer Institut, Human Resources Management, Nicole Schubert, 5232 Villigen PSI, Switzerland