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, nanofabrication, and computational electromagnetism. Strong coding (Python /MATLAB) and experimental aptitude is desirable.
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/Simulink/Python for modelling, simulation, and control design. Experience with genset systems, hybrid powertrains, or real-time control applications is highly desirable. A practical interest in system
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or machine learning. Excellent programming skills (e.g., MATLAB, Python, or ROS), a strong publication record, and an ability to work collaboratively in multidisciplinary environments are essential. Prior
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area, have extensive experience in conducting model-based economic evaluations using suitable statistical software (e.g. R or Python) and the ability to work independently, prioritise your own workload
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area, have extensive experience in conducting model-based economic evaluations using suitable statistical software (e.g. R or Python) and the ability to work independently, prioritise own workload and
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assistantship. The ideal candidate will have a strong understanding of NLP, machine learning, and AI ethics, with proven skills in Python and frameworks like TensorFlow or PyTorch. Preference may be given
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experience in developing computational models and implementing models for computer simulations. Software development in C++ and/or Python is expected, and experience in model analysis and parameter
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experience in developing computational models and implementing models for computer simulations. Software development in C++ and/or Python is expected, and experience in model analysis and parameter
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and administration. Your profile: Completed Master's / Diploma degree in the field of Astrophysics Extensive programming knowledge (Python) Excellent command of written and spoken English (C1 level
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with coding, ideally in Python or MATLAB Funding support This studentship is open to Home students only. It is jointly supported by the Faculty of Engineering and industrial partners which is expected