156 machine-learning-"https:"-"https:"-"https:"-"UCL"-"UCL" Postdoctoral positions in United Kingdom
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), working closely with Professor Catrin Tudur Smith and Dr Ahmed Waqas. The Postdoctoral Researcher will work on a network meta-analysis of psychosocial interventions for military personnel with Posttraumatic
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current accreditations and commitment to Equality, Diversity and Inclusion here , including our commitment to the Armed Forces Covenant . Further information Please contact Dr Mark Wood, m.e.wood
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About the Role This is an exciting position where applicants are invited to join a multi-disciplinary team of bioengineers, biomedical scientists, and computer scientists working together at Queen
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: Experience implementing Quantum Monte Carlo methods. Experience applying Machine Learning methods to scientific problems. About the School The School of Physical and Chemical Sciences is one of the UK’s elite
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About the Role This is an exciting position where applicants are invited to join a multi-disciplinary team of bioengineers, biomedical scientists, and computer scientists working together at Queen
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About the Role This is an exciting position where applicants are invited to join a multi-disciplinary team of bioengineers, biomedical scientists, and computer scientists working together at Queen
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About us: We are seeking to appoint a postdoctoral research associate with an excellent track record in semantic technologies and machine learning. Topics of interest in this area include, but
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for manufacturing operations. Process control: process modelling, control, and optimization, with applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in
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tablet based cognitive screening tools for use with those with acquired brain injuries (e.g., stroke, traumatic brain injury etc). The post-holder will be expected to be central in data collection in
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We have an exciting opportunity for a Research Assistant/Associate to make a contribution to an ERC-funded project "Dynamic network reconstruction of human perceptual and reward learning via