207 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" positions at University of Nottingham
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rapidly growing UK Clinical Research Collaboration registered Clinical Trials Unit (http://www.ukcrc-ctu.org.uk) based in the School of Medicine at the University of Nottingham. Our mission is to conduct
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. The University of Nottingham offers a wide range of employee benefits. More information can be found at: https://www.nottingham.ac.uk/hr/your-benefits/a-z-of-benefits/benefits-a-z.aspx As part of our commitment
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& Management. He also works closely with industries such as Alibaba/Taobao, Duckbill Logistic Technology and cross-border e-commerce companies. For details of the PI, please refer to the link: https
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and travel schemes Find out more on our benefits website: https://www.nottingham.ac.uk/jobs/benefits-and-facilities/your-benefits.aspx What next Further information is available in the role profile
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mornings. Further details will be given at interview. All of our vacancies are available to view at: https://www.nottingham.ac.uk/jobs/home.aspx All staff employed at Levels 1-3 will be eligible to claim
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unit and individual and collaborative research in the area of Power Electronic, Machine and Control. The role holder will be expected to conduct and lead high-caliber, impactful research at the forefront
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. What you should have: A 1st degree in physics or engineering. An interest in optics, some ability in computer programming A desire to learn new skills in complementary disciplines. You will work jointly
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for the management of modules needed by new Academics across Faculties for qualification/accreditation to teach in the UK higher education system. The programme and material for the teaching and assessment
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for the transition from fossil carbon towards a sustainable net-zero future, as well as growth and sustainability of the UK economy and beyond. https://www.nottingham.ac.uk/news/c-loop-ukri C-Loop is a collaborative
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Subject area: Drug Discovery, Laboratory Automation, Machine Learning Overview: This 36-month PhD studentship will contribute to cutting-edge advancements in automated drug discovery through