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deep learning, with a sound understanding of experimental research methodology documented through coursework, projects, or publications. You must have strong programming skills in Python and experience
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example through relevant work experience and/or peer-reviewed academic works. Experience in mechanical testing Experience with programming in Python or Matlab Strong analytical and problem-solving skills
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/phd ) Documented experience with Python or another relevant programming language, or with computational materials science/chemistry. Good oral and written presentation skills in English. PLEASE NOTE
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optimization. Strong programming skills (Python, Julia, Jax). Experience with numerical optimization is also desirable. Personal characteristics To complete a doctoral degree (PhD), it is important that you are
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, structure preserving deep learning, stochastic differential equations, generative AI, numerical optimization. Strong programming skills (Python, Julia, Jax). Experience with numerical optimization is also
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. Experience in mechanical testing Experience with programming in Python or Matlab Strong analytical and problem-solving skills Excellent oral and written presentation skills in English The appointment is to be
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meet the requirements for admission to the faculty's doctoral programme in Engineering Cybernetics . Strong programming skills, in particular Python, and practical experience with modern machine learning
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, Python, or a similar programming language. English language skills, both written and spoken, corresponding to the scale C1 in the Common European Framework of Reference for Languages (CEFR). See which
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(Python, C++, etc.). Experience in mathematical programming and/or optimization software such Pyomo, GAMS or similar. Proficiency in process simulation software (Aspen Plus, Aspen HYSYS, etc.). Experience
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background and research-oriented master thesis in a related field (e.g., signal processing, statistical machine learning, applied mathematics); Significant experience with programming (preferably Python). Good