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, nanofabrication, and computational electromagnetism. Strong coding (Python /MATLAB) and experimental aptitude is desirable.
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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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-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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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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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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). Experience in numerical modeling and data analysis. An interest in groundwater contamination, risk assessment, and sustainability. Programming experience (Python, MATLAB, or similar) is desirable but not
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in working in public health or epidemiology or similar is desirable. Knowledge and evidenced experience of data science analytical packages and R or Python would be advantageous. Funding The funding
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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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laboratory-based skills Programming skills (Matlab, Python, or similar) Applicants with a good 2.1 degree are also encouraged to apply if they can demonstrate excellent laboratory skills through previous
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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