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system measures) using Matlab, Python or similar software tools. You have affinity with, or experience in, virtual reality serious game design and user experience (UX) assessment. You have affinity with
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probabilistic modeling Good programming skills in Python/C/C++ Good oral and very good written skills in English Enjoys working in an international and inter-disciplinary research group TU Delft (Delft University
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++, Python or Matlab). Ability to work in an interdisciplinary team and interested in collaborating with industrial partners. Motivated to develop your teaching skills and coach students. Fluent in spoken and
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requirements Required: MSc degree (or equivalent) in Aerospace Engineering, Air Transport, Operations Research, or related field Strong analytical and modeling skills Proficiency in programming (such as Python
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communication skills and are able to work in a multidisciplinary team. You have strong programming skills (e.g., C++, Python, …). You are creative, critical, analytical, motivated and persistent. You have a good
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related discipline. A solid background in de novo protein design, protein structure prediction (Rosetta, AlphaFold, …), protein expression, structure elucidation, machine learning, C/C++ and/or Python with
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Engineering, Physics or similar is required Knowledge of at least one programming language is expected: Python, Matlab, Fortran, C++, … Experience and/or keen interest in transport modeling of porous systems
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field Has strong interest in methodological research in healthcare Has experience with NLP and/or language modeling techniques Has solid programming skills (e.g., Python) Is motivated to work at the
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-Carrier Energy Hubs (MC-EHs), where multiple energy generation, conversion, and storage technologies across diverse carriers integrate smartly and locally, show promise for overcoming such barriers
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insights. Information Statistical modelling of multiple omics datasets is a lively and rapidly developing research area. Ongoing technological advances make it possible to measure multiple biological data