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control of power converters Experience or coursework in device simulation tools (e.g., MATLAB and Ansys) is a plus. Strong interest and willingness to learn experimental techniques for device fabrication
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., MATLAB and Ansys) is a plus. Strong interest and willingness to learn experimental techniques for device fabrication and characterization. Experience with development of experimental setup. Proficiency in
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, Agent-based, and Supply chain simulation Required skills Demonstrated knowledge of software like Plant Simulation, AnyLogic, AnyLogistix, or the like Fluency in either MATLAB, Lingo, Python, R, SmartPLS
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didactic qualifications and competences in accordance with level of appointment Ability to independently design, set up, and run experimental studies, including the relevant programming skills (e.g. Matlab
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written and spoken English. Fluent in a computer coding language (python or Matlab or C++ or etc). The Scientific environment We offer creative and stimulating working conditions in a dynamic and
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possible. It is strictly required that you have experience with: Scientific programming, preferably in python and/or MATLAB and/or C++ Derivation and implementation of finite element methods (FEM) in code
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also be able to demonstrate excellent ability to code with or learn computer programming languages, such as C++, C#, Python, and/or Matlab. A desire to engage in cross-disciplinary research
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. in C/C++, Python, Matlab and Qt). Strong mathematics skills and practical knowledge in 3D modelling. The candidates are also expected to have the following qualifications: Ability to work independently
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, preferably Reinforcement Learning (e.g., Q-learning, Deep Q-Networks) or other control algorithms. Proficiency in Python, MATLAB, or similar for data analysis, modeling, or AI implementation. Strong written
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, MATLAB, and/or C++/C#) Knowledge of machine learning techniques, particularly for time-series data Background in prosthetics or human-machine interfaces is advantageous PhD Stipend 2: Adaptive Control