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advanced numerical simulation and/or optimization tools to the design and characterization of the facility; interact with other technical groups working on the Diamond-II design (e.g. Engineering
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optimality with computational efficiency. Reinforcement Learning through Stochastic Control. We will develop methods from stochastic control, which will provide a mathematically grounded approach that has a
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Senior Technicians will be responsible for supporting these venues, and the wider building, ensuring optimal management and coordination of the facilities and providing a high quality of technical
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medicine, with a primary focus on optimizing clinical trial design. The partnership will bring together the University of Oxford’s expertise in statistics, mathematics, engineering and AI with industry
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the most pressing areas of fundamental understanding which are currently lacking and need to be overcome in order for the four PV device concepts to be optimized. The modelling findings on a range of
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to work both independently and as part of a team and have good communication skills. In this role, you will refine and optimize methods for the directed differentiation of human embryonic stem cells
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medicine, with a primary focus on optimizing clinical trial design. The partnership will bring together the University of Oxford’s expertise in statistics, mathematics, engineering and AI with industry
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, large-scale, embedded, robust and distributed optimisation, polynomial/sum of squares methods, and optimal, robust and model predictive control, as well as a wide range of applications spanning biology
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community. You will manage the imaging facility and its equipment, ensuring its optimal performance and accessibility, and oversee the microscopy Small Research Facility (SRF). This position is based
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to the development of novel strategies for neuronal analysis in health and disease and optimizing new methods. The project is funded by the Motor Neuron Disease Association for 3 years. Please see the below 'Job