286 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" positions at University of Glasgow
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ability as appropriate. C4 Highly motivated, ability to use initiative and quick to learn new techniques. C5 Excellent communication skills (oral and written), including public presentations and ability
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(STEMM) employment in academia. https://www.gla.ac.uk/schools/bohvm/athenaswan/ The College of Medical, Veterinary and Life Sciences (MVLS) has 8 Schools that bring staff together around thematic strengths
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may be eligible to be sponsored under the Skilled Worker visa route if tradeable points can be used under the Skilled Worker visa rules. For more information please visit: https://www.gov.uk/skilled
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days) and August (approx. 15 days). Dates for this academic year are available on the Registry webpage: https://www.gla.ac.uk/myglasgow/registry/staff/exams/dates . As a valued member of our team, you
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, machine learning, and related AI approaches, this is your chance to work at the intersection of data science, pathogen-research and immunology, tackling questions that matter for global health. The position
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. Please note that this post may be eligible to be sponsored under the Skilled Worker visa route if tradeable points can be used under the Skilled Worker visa rules. For more information please visit: https
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related to this. Further information is available at : https://www.mygov.scot/pvg-scheme We believe that we can only reach our full potential through the talents of all. Equality, diversity and inclusion
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. For more information please visit: https://www.gov.uk/skilled-worker-visa. As a valued member of our team, you can expect: 1 A warm welcoming and engaging organisational culture, where your talents
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An excellent employment package with generous terms and conditions including 41 days of leave for full time staff, pension - pensions handbook https://www.gla.ac.uk/myglasgow/payandpensions/pensions/, benefits
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to the development and implementation of standardised tools, templates, and systems to enhance project delivery and continuous improvement and identify opportunities for process enhancement, drawing on lessons learned