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ability to engage with complex data challenges will be greatly valued. Experience with Python or AI frameworks is a plus but curiosity, creativity, and enthusiasm are equally important. You will join a
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requirements: Excellent analytical skills Strong verbal and written communication skills Desirable: Strong proficiency in optimising and modelling power and energy systems Programming skills in Python and Julia
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such as Matlab and/or Python. How to apply Please send an email with subject “PhD studentship: Numerical simulation of boiling flows for high heat flux fusion components” to Dr Mirco Magnini, mirco.magnini
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: Comparative transcriptomics, orthology inference, positive selection detection, protein domain analysis, phylogenetic comparative methods Computational skills: UNIX/Linux, HPC computing, R, Python You will gain
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programming skills in Python/MATLAB, and an interest in digital twin technologies, cybersecurity and machine learning. Entry Requirements Acceptable first degree: Computer Science or related disciplines
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cell and spectroscopic analysers. Programming (e.g., R, Python) and machine learning for advanced atmospheric time-series analyses. Skills for presenting research at conferences and writing peer-reviewed
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requirements for our PhD programme . Skills in Python, C++ or ROS are preferred. How to apply Applications should be submitted via the Robotics and Autonomous Systems PhD programme page. In place of a research
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projects related to these research spaces as well, especially if projects are linked to the research aims mentioned in the previous paragraph.Ideal candidate:- extensive experience in programming in Python
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, Urban Studies, Urban Analytics, Environmental Science, Computer Science, Architecture, or an appropriate master’s degree. Familiarity with Python/R programming, GIS and spatial analysis (e.g., ArcGIS
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professional networks. Candidate’s profile Knowledge of quantum computing and an understanding of challenges of building large-scale systems Programming skills in Python A good Bachelor’s Hons degree (2.1