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of the following: A solid foundation in programming (particularly Python) and modern machine learning frameworks (e.g., PyTorch, TensorFlow). An interest in AI security, trustworthy ML, or the reliability of ML
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programming, e.g., in Python, PyTorch, TensorFlow, or similar. Curiosity and willingness to work with researchers from a heterogeneous group, with core expertise in communication theory, networking, information
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programming in Python and the modern AI ecosystem, including PyTorch, HuggingFace, and ONNX and you are comfortable working systematically with complex technical problems. Experience with industrial
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programming (particularly Python) and modern machine learning frameworks (e.g., PyTorch, TensorFlow). An interest in AI security, trustworthy ML, or the reliability of ML systems in safety-critical settings
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-Mechanical System Design, or a related field Experience with modelling of mechanical and hydraulic systems Ability to develop and analyze dynamic system models using MATLAB/Simulink and Python or similar tools
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-physical systems, energy systems, or smart buildings Good programming skills (Python, MATLAB, or similar) Excellent communication skills in English Who we are The PhD Fellow will be affiliated with
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in Python, C++, MATLAB/Simulink, ROS, Gazebo or other simulation and robotics frameworks. Experience with CAD/CAE, CFD, digital twins, embedded systems or experimental data analysis is an asset
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communication, political behavior, political psychology, or a closely related area. An affinity to computational tools and methods, and strong programming skills (e.g., Python and/or R). Familiarity with research
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using environments like MATLAB or Python, which you apply to tasks such as optimisation, parameter studies, or processing of measurement data. You enjoy working experimentally with antennas and are
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frameworks. Further, it would be advantageous for applicants to demonstrate proficiency in at least one scientific programming environment such as Python, MATLAB, or R. A good understanding of hydrodynamic