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BBSRC Yorkshire Bioscience DLA Programme: Harnessing JAK-STAT signalling for optimal innate immune cell function School of Medicine and Population Health PhD Research Project Competition Funded
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, advanced statistical methods and the potential to develop pioneering reconstruction and calibration techniques involving machine learning. The PhD will prepare equally well for a career in industry and
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also be joining the Leonardo Centre for Tribology, which is an active and friendly group. There are ~25 PhD students working on machine elements, tribology, lubrication, and sensor systems for wind, auto
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expertise in machine learning, soil microbiomes, microbial 3D printing and biophysics, our team has access to a broad spectrum of techniques and practical know-how. This is therefore an exciting opportunity
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treatment window may already have passed. Project Aim: This project proposes the development of an innovative approach that applies computer vision and machine learning to detect early signs of stroke through
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data acquisition. • Computational techniques, including machine learning and statistical inference. • Collaborative research at the interface of mathematics, biology, and physics. Why us? The
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happen is not straightforward, and success is far from guaranteed. Using AI as a tool for scientific research requires deep knowledge of both the subject area being studied and the AI and machine learning
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, combining the radio frequency (RF) circuitry of a transceiver with the digital processing needed for machine learning, all in a single microchip. Next generation wireless devices will not only send and
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potential competitive edge. In this PhD the student will learn advanced photonic design, nanofabrication, and heterointegration techniques. The project involves creating nanostructured 3R-MoS₂ and integrating
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for attaining desired engineering properties. The project will combine physical modelling, experimental data, and machine learning to create a feedback loop that refines the material properties and manufacturing