job description
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Are you fascinated by fundamental flow physics? Are you inspired by combining physics-based models with machine learning techniques? Are you passionate about programming and high performance computing? Are you eager to collaborate with industrial partners?
We are looking for a motivated PhD candidate who will combine model-based (physics) and data-driven (machine learning) approaches to develop innovative, highly accurate and efficient solvers for thin gas flows.
Computational Fluid Dynamics is a key enabler of science and many major societal challenges. Many key advanced and emerging technologies require unprecedented control of heat and mass transfer in flows ranging from continuous to highly dilute states, often with electromagnetic fields, chemical reactions, and complex interactions with boundaries. Due to the non-equilibrium nature of dilute flows and the pronounced influence of molecular effects, these transport processes are highly complex and occur under non-standard conditions. In this project, you will pave the way for an emerging technology approach to modeling dilute flows by developing innovative methods that blend data-driven (machine learning) and model-driven (physics-based) approaches. You will work in a consortium of university groups with complementary skills in fluid dynamics and statistical physics (Fluids and Flows, TU/e) and machine learning techniques (AMLab, UvA), and commercial partners in need of these new approaches.ASML is a leader in high-resolution lithography solutions, Flow Matters specializes in consulting on dilute flow solutions /Licensing, Carbyon develops direct air capture systems and they will provide expertise, data and experiments and will be the primary validators and first users of the novel solutions.
offer requirements
We are looking for enthusiastic and highly motivated PhD students with an excellent background in fluid dynamics, computational physics and high performance computing.
A master’s degree (or equivalent university degree) in (applied) physics, mechanical engineering or a related field.
Research-oriented attitude.
Familiarity with computational fluid dynamics methods such as DSMC, LBM or PiC as well as parallel programming.
Ability to work in a team and interest in collaborating with industrial partners.
Fluent in spoken and written English.
offer benefits/salary
A rewarding career in a dynamic and ambitious university, in an interdisciplinary environment and within an international network. You will work on a beautiful green campus within walking distance of the central train station. In addition, we offer you
Full-time employment for four years, with a mid-term evaluation (go/no-go) after nine months. 10% of your working time is dedicated to teaching duties.
Salary and benefits (e.g. pension scheme, paid pregnancy and maternity leave, partially paid parental leave) according to the Dutch Universities Collective Labor Agreement, level P (minimum 2,872€, maximum 3,670€).
8.3% year-end bonus and 8% annual vacation pay.
High-quality training programs and other support to help you grow into a self-aware, autonomous scientific researcher. At TU/e, we encourage you to learn on your own.
State-of-the-art technical infrastructure, on-campus nursery and sports facilities.
Subsidized commuting, work-from-home and internet costs.
Employee immigration team and tax compensation program for international candidates (30% facilitation).