As newly appointed faculty member, you will be working in the Center for Analysis, Scientific Computing and Applications (CASA) of the Department of Mathematics and Computer Science (M&CS) at Eindhoven University of Technology (TU/e). Besides your research quality, your educational skills are very important. You will contribute to the curricula of the TU/e Department M&CS, for both Mathematics, Computer Science and Data Science, and with a
keen eye on curriculum wishes and needs in combining data- and model-driven approaches in computational science in other TU/e departments.
Computational science is of vital importance to today’s and tomorrow’s society. It enables the simulation of processes, phenomena and systems that cannot be studied by real experiments, because these are too dangerous, too expensive, unethical, or just technically impossible. Moreover, as opposed to experiments, computational science allows for automatic design and optimization (inverse computations). Within CASA, we propose, analyze, develop and implement new computational techniques and carry these over to among others: energy research
(to offshore wind farm aerodynamics and tokamak plasma dynamics for instance), optics research (for illumination and nanolithography), and quantum and molecular dynamics research.
Traditionally, computational science is model-driven; based on for instance mathematical models of physical laws. Because of the immense growth in the availability of data, computational science is becoming more and more data-driven, with a crucial role in this for machine learning. Promising examples of successful use of machine learning in computational science already exist, for instance recognition of crystal structures by neural networks. Within CASA, in the context of MSc and PhD research, examples are being studied of neural-network technology as components of computational-science setups. The potential of the use of data and machine learning in computational science, in combination with the use of models (first principles), is enormous. An important goal of our new full professorship Data-Driven Computational Science is to further develop machine learning in the context of computational science, bridging data science and computational science; combining data- and model-driven approaches, hand-in-hand with the development of more theory for a rational and trustworthy use of data and machine learning in computational science.
Information and application
Eindhoven University of Technology is a top-ranking Dutch university that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and prominent position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for highly complex problems of today and tomorrow.
Questions regarding the scientific content can be directed to prof.dr.ir. Barry Koren,
For information about terms of employment, please contact the recruiter,
Ms. Elly van den Eertwegh, e.a.m.v.d.eertwegh[at]tue.nl or + 31 (0)6 39186476).
Are you inspired to know more about working at TU/e? Please visit www.tue.nl/jobs or look
at our video:
The application should include a:
We are looking forward to your application and will screen it as soon as we have received it. Screening will continue until the position has been filled, and applications will receive full consideration.