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, preferably in R or Python; Have, or will shortly acquire, a quantitative master's degree (for example, in Health Economics, Econometrics, Technical Medicine, Industrial Engineering, Biomedical Engineering
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) communication and networking technologies, embedded system design, and computer programming (C++, Python, etc.). Ability to work in an interdisciplinary team and interested in collaborating with industrial
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, surveys, meta-analyses, cost-benefit analysis you have some experience with chosen coding language, such as R or python you are enthusiastic about communicating research to academic and non-academic
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one programming language: Matlab, Python, is expected. Eager to work within a team and independently. Ability to collaborate with industry and academic researchers. Fluent in spoken and written English
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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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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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++, 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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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