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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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tools (STATA, R, or Python). Assist in literature reviews and summarising academic research. Contribute to writing research papers and policy reports. Participate in meetings with collaborators and
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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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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
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or Abaqus (or willingness to learn) General knowledge of structural analysis and material behaviour, especially failure mechanisms Some experience with coding, ideally in Python or MATLAB Funding support This
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-field methods) Multiscale mechanics and microstructure-property relationships Python/C++/Matlab-based simulation and data analysis Industry-facing research and technology transfer You will also benefit
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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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will be an advantage if candidates have an interest in optimisation, control and computing systems, model checking, mathematical logic and good programming skills, ideally in MATLAB, Python and/or C/C
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languages such as Python for data analysis and simulations. Experience with optical systems, astronomical observations, or satellite tracking would be advantageous, although not compulsory. Strong analytical
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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