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Field
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(essential), Modelling and resource analysis (essential), Use of Python, Matlab or other appropriate programming languages (essential), Familiarity with building and construction (desirable). Collaboration and
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Experience Experience developing research software using appropriate languages and environements (Python, Julia, Matlab) Knowledge of optimisation problem formulations and solution methods Experience of risk
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relevant Master's degree (or exceptional Bachelor's) in biomedical/mechanical engineering, materials science, or computer science, with experience in mechanical design/textiles and programming (Python/MATLAB
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. Strong quantitative skills, with experience in econometrics and statistical analysis. Experience working with large datasets and appropriate software (e.g., Stata, R, Python, Julia, MATLAB). Excellent
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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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, nanofabrication, and computational electromagnetism. Strong coding (Python /MATLAB) and experimental aptitude is desirable.
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deep learning, generative models, or biomedical imaging/omics data Strong programming skills (Python, PyTorch, etc.) A commitment to interdisciplinary collaboration and impactful research How to Apply
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placement locations. Advanced metaheuristic optimisation algorithms, implemented in Python and interfaced with DIgSILENT PowerFactory, will be developed to determine the most effective PST locations and
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of the position. Equivalent research experience will also be considered. You should have familiarity in handling large and complex datasets and skilled in programming languages such as R or Python. The ideal
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latitudes. Student profile: The project requires the student to be relatively proficient in Python programming to use and modify existing software, as well as for potentially developing new diagnostics and