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Role: Postdoctoral Research Associate – Nonlinear and Time-Varying Photonic Systems Grade and Salary: Grade 7 - £37,694 - £47,389 FTE and working pattern: Full-time (35 hours per week), Fixed for 12
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central to how we understand mental health; Work in partnership with affected communities. About the role This is an opportunity to do important research on mental health, work and the benefits system
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Details of the role: Reports to: Michael Way – Group Leader Working pattern: This is a full-time fixed term position for 4 years on Crick Terms & Conditions of Employment Application closing date
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Details of the role: Reports to: Michael Way – Group Leader Working pattern: This is a full-time fixed term position for 4 years on Crick Terms & Conditions of Employment Application closing date
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The University of Oxford is a stimulating work environment, which enjoys an international reputation as a world-class centre of excellence. Our research plays a key role in tackling many global
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central to how we understand mental health; Work in partnership with affected communities. About the role This is an opportunity to do important research on mental health, work and the benefits system
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Nanotechnology under the supervision of Prof. Rashid Ganeev . The members of our laboratory work on the applications of lasers for material science, nonlinear optics, and nanotechnologies. The studies will include
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fibre lasers. Our work is a mix of experimentation and numerical modelling. We use different materials, laser beam geometries and nonlinear effects, to create new light sources for a multitude of
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
between nonlinear control theory and machine learning to provide formal guarantees on performance, safety, and robustness of complex systems. We are a part of the Finnish Center for Artificial Intelligence
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part-time post (0.2FTE) ideal for someone working in industry or with industry experience. This is because we want to bring in expertise with data processing and machine learning pipelines, and their