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Field
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field. A background in organic chemistry, and/or high-throughput experimentation is desirable. Proficiency in programming languages (Python/MATLAB) commonly used in machine learning applications is
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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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/ physics/ meteorology/ engineering/ biology. Experience in a computer programming language (e.g. Fortran, Python). A general understanding of the importance of the scientific method is essential. A previous
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engineering. Expertise in numerical tools (Ansys, JMAG, .etc) and programming are desirable. Experience in electrical machine prototype development would be advantageous. Eligibility and Application
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have a 1st class degree (BEng or MEng/MSc) in electrical/mechanical engineering. Expertise in numerical tools (Ansys, JMAG, .etc) and programming are desirable. Experience in electrical machine
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degree in Engineering and have an interest in and/or a good understanding of numerical modelling and testing of structures. Prior knowledge of finite element methods and programming (e.g. C++, Python
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repair and maintenance of gas turbine engines. Applicants are invited to undertake a fully funded three-year PhD programme in partnership with Rolls-Royce to address key challenges in soft robotics
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will have programming experience, particularly on the development of machine learning pipelines. The University actively supports equality, diversity and inclusion and encourages applications from all
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process It is anticipated that the selection process will take place on 8th July. This will consist of an interview, test and tour. We plan to let candidates know if they have progressed to the selection
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, or related disciplines. Skills in numerical tools and programming are desirable. Any experience in engineering design or manufacturing would be advantageous. Eligibility and Application Due to funding