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Applications are invited from PhD studentship candidates with good first degrees in computer science, physics, maths, biology, neuroscience, engineering or other relevant disciplines to join
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algorithms based on neural activity data (local field potentials, LFPs) from key deep brain stimulation targets including the basal ganglia and thalamus. Auxiliary data available to implanted devices include
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Deadline: All year Round How to apply:uom.link/pgr-apply UK only This PhD studentship is open to Home (UK) EU applicants with pre-settled status (funded by TWI Ltd). The successful candidate will
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The PhD studentship will be based at the University of Cambridge in the Department of Materials Science and Metallurgy as part of the Structural Materials Group. The Structural Materials Group is a
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This self-funded PhD opportunity explores assured multi-sensor localisation in 6G terrestrial and non-terrestrial networks (TN–NTN), combining GNSS positioning, inertial systems, and vision-based
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This PhD project aims to achieve a breakthrough in thermal efficiency (>50%) for dual-piston Free-Piston Engine Generators (FPEGs). The research will pioneer a novel, integrated methodology
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interference, while ensuring energy-efficient and scalable operation. This PhD project will focus on developing machine learning algorithms to enable robust channel estimation, intelligent user association
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The Medicines And Healthcare Products Regulatory Agency; | Canary Wharf, England | United Kingdom | about 2 months ago
of CPRD's interventional research services. Responsibilities include defining the strategy and implementing standard methods and algorithmic approaches to data capture, transformation and export; undertaking
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Develop practical, industry-transforming technology in this hands-on PhD program focused on immediate industrial applications. This exclusive opportunity places you directly at the interface between
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sustainability goals whilst improving operational efficiency? This PhD studentship will involve developing machine learning models, creating virtual manufacturing replicas, and implementing optimisation algorithms