26 phd-position-data-mining Postdoctoral positions at University of London in United Kingdom
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Technology Laboratory (DSTL), Electromagnetic Environment (EME) Hub. About You Applicants should have a PhD in modelling hypothetical scenarios, with and without data, for structured decision-making under
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multi-modal data, mitigation for hallucinations and biases. For details see the project website and in particular workstreams 2,3 and 5. About You Candidates must have an Undergraduate Degree in
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will plan and conduct experiments, generate high-quality data, prepare publications, make presentations and help supervise associated PhD students. The successful candidates will join large, supportive
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including cell culture, organ-chip models, tissue engineering, and musculoskeletal biology. The PDRA will plan and conduct experiments, generate high-quality data, prepare publications, make presentations and
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researchers and industrial collaborators on the research project. About You The candidate should have a PhD (or close to completion) in a biological, biomedical or closely related science. Previous work
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Right to work: Applications from job seekers who require sponsorship to work in the UK are welcome and will be considered alongside all other applications. For further information visit the UK Visas
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Right to work: Applications from job seekers who require sponsorship to work in the UK are welcome and will be considered alongside all other applications. For further information visit the UK Visas
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to work: Applications from job seekers who require sponsorship to work in the UK are welcome and will be considered alongside all other applications. For further information visit the UK Visas and
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the successful candidate for this position. Therefore, the appointable candidate will need to be eligible to work in the UK or have leave to remain in the UK and associated right to work for the duration
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of computational and behavioural neuroscience with modelling and domestic chicks’ data. This position is funded by a Leverhulme Trust project entitled “Generalisation from limited experience: how to solve