296 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" Postdoctoral research jobs in United Kingdom
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experiments in gelatine (https://doi.org/10.5194/egusphere-egu25-9211). This model will be tested with analogue experiment results from the MAGMA Lab, run by other members of the project team. The second
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project can be found here: https://www.imperial.ac.uk/bio-sustainable-materials/ VALUED is aiming to demonstrate the development of functional materials derived from bio-renewable resources. Several
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research project lead by Oxford Materials (Professors Robert House (PI), Saiful Islam, Peter Bruce), with UCL Chemical Engineering (Dr Rhod Jervis) and 4 industrial partners that brings together expertise in
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also have a chance to instruct Doctoral researchers and Master thesis candidates and develop towards a more independent position. Background and expertise We are looking for candidates who understand
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the Department of Physics. Machine learning has made enormous progress during recent years, entering almost all spheres of technology, economy and our everyday life. Machines perform comparably to, or even surpass
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of competitive benefits available to all staff for both work and personal life - https://hr.admin.ox.ac.uk/staff-benefits For informal enquiries about the post, please contact Ellie Tzima – ellie.tzima
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computer-aided design (CAD) and FEM solvers of optical systems Experience in the optical and mechanical design of optical devices or lasers Experience with construction and testing of optical cavities
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of Salivary Cortisone Test (Re-SCAIT) study (funded by NIHR Health & Care Services Delivery Research (HSDR) https://fundingawards.nihr.ac.uk/award/NIHR174395 ) will evaluate the implementation and uptake
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information: Interviews are planned for 16th of March 2026. For further information and details of how to apply, please visit our website http://jobs.jic.ac.uk or contact the Human Resources team on 01603
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undergoing significant growth with substantial investment in new appointments, research infrastructure and laboratory space refurbishment. Further details are available at www.kcl.ac.uk/nmes and http