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-throughput experimentation is desirable. Proficiency in programming languages (Python/MATLAB) commonly used in machine learning applications is desirable but learning can be completed during the PhD. Excellent
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programming and data analysis (e.g. Python, Julia, MATLAB, C/C++, or similar) • Ability to work independently and as part of a collaborative research team Desirable skills / experience
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, mathematics, or related scientific disciplines. Skills in numerical tools and programming are desirable (MATLAB, python, C++ etc). Any experience or capabilities in engineering design or manufacturing methods
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related discipline. Good programming skills (e.g., Python, PyTorch, TensorFlow). A genuine interest in pushing the boundaries of efficient and deployable AI. Prior research experience (e.g., project work
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. Desirable Skills (an advantage, not a requirement) Data analysis skills in python. An interest in energy policy / the economics of energy. Numerical modelling. Eligibility This studentship is available for UK
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/teaching experience. The confidence to deal with uncertainty and tackle any problem without a defined final answer. Desirable Skills (an advantage, not a requirement) Data analysis skills in python. Granular
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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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languages (Python/MATLAB) commonly used in machine learning applications, is desirable but learning can be completed during the PhD. Excellent communication and interpersonal skills to facilitate
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(ioan.notingher@nottingham.ac.uk ). Application: https://www.nottingham.ac.uk/pgstudy/how-to-apply/apply-online.aspx View All Vacancies
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transcripts. These should be submitted via email to Dr Taresco and through the University of Nottingham’s online application system (https://www.nottingham.ac.uk/pgstudy/how-to-apply/apply-online.aspx