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Applications are invited for a fully-funded 3-year PhD studentship based in the Department of Clinical Neurosciences at the University of Cambridge under the supervision of Dr Topun Austin starting
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. Familiarity with standard design verification (DV) procedures and continuous integration (CI) setups would be beneficial. Knowledge of machine learning workloads and the design of machine-learning accelerators
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Possession of, or near completion of, a PhD in Law, or equivalent professional legal experience Ability to teach Land Law and at least one additional subject area Priority will be given to applicants who can
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completion, preferably with an application of their research in a real-world setting. Coding and software engineering proficiency will be expected if relevant to their experience, e.g. for machine learning
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fixed-term post, and is to provide cover during the absence of another staff member. This post requires teaching expertise at a level that is at the forefront of academic practice. Ability to teach
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), electrophysiology (EEG), interventional (TMS, tDCS) and neurocomputational (machine learning, reinforcement learning) approaches to understand the network dynamics that support learning and brain plasticity
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is to provide cover during the absence of another staff member. This post requires teaching expertise at a level that is at the forefront of academic practice. Ability to teach central topics
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machine learning tools and working on Linux High-Performance Computing platforms would be highly desirable. This is a highly collaborative role and you will work with scientists and clinicians from other
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). The successful candidate will have or be about to receive a PhD in a relevant subject area such as, but not limited to psychology, cognitive neuroscience, engineering, physiology, or audiology. Experience in
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management studies. The Marketing group at CJBS comprises scholars specialising in marketing strategy and modelling, including econometrics, machine learning, and analytical approaches. In