25 machine-learning "https:" "https:" "https:" "https:" positions at University of Surrey
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covering all major compliance domains – including fire safety, water hygiene (L8), asbestos (CAR 2012), electrical and mechanical testing, LOLER / PUWER inspections, and DSEAR activities. This role requires
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of conventional and CNC machine tools, together with an understanding of Health and Safety legislation in a workshop setting, is essential. Degree Apprenticeship Route: We are also pleased to offer this role as
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, physiology and general medicine, and specialities. The first year of the course is structured in themes, based around clinical cases, which enables medical students to learn clinically relevant biomedical
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requirements of the role. If you’d like to learn more about the role, please contact: Sarah Heisig (Technical Manager) s.heisig@surrey.ac.uk. Interviews will be held during February.
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working knowledge of relevant software tools (e.g.Linux, python, C/C++ & html programming and PC computer networking) Experience of CubeSat mission operations covering mission development from concept
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(early evenings and weekends) but shift patterns are provided well in advance. You should be confident in your use of Microsoft packages such as Outlook, Word, Excel and Teams with the ability to learn
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service standards. This is a role for an exceptionally organised individual with excellent attention to detail and the ability to prioritise to meet often conflicting deadlines. The ability to learn quickly
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relevant defective information and repairs. All defects to be reported immediately to the help desk for further action. Must be computer literate and work well with computer/tablet systems What’s in it for
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to neurodevelopmental conditions caused by prenatal alcohol exposure, with a UK prevalence estimated at 3.2%, among the highest globally. Individuals with FASD commonly experience challenges with learning, memory
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dynamically varying propagation conditions. You will learn and develop boundary integral equation (BIE) formulations for Maxwell’s equations; Adjoint-based optimisation methods for wave problems; Statistical