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(e.g. Python, MATLAB, R or similar) Ability to develop and apply models of complex systems, simulation and stochastic modelling, optimisation under constraints Desirable skills and training in one
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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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Labview or Python Hands on experience of maintaining equipment related to electrical characterization of semiconducting materials, including probe stations, cryogenic cooling and vacuum pumps Documented
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modeling/simulation tools (e.g., MATLAB/Simulink, Modelica, and COMSOL Multiphysics), energy systems analysis/optimization/programming software (e.g., HOMER, GAMS, and Python). Evidence of previous
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methodology is essential. Demonstrated strong proficiency in programming (e.g., Python, PyTorch/JAX, or similar) and computational skills are required for this position. Candidates must have excellent
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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
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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
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engineering disciplines, including structural mechanics, hydrodynamics and machine learning Strong programming skills in Python and/or MATLAB Experience with scientific computing, CFD/FEM software, potential