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whole-brain scale analysis of multimodal features such as connectivity, morphology or cell ultrastructure. Of particular interest here are two related problems: systematic meta annotation (especially cell
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) uses principles from systems neuroscience to develop reliable, low-power spiking neural networks and learning algorithms for implementation in a new generation of neuromorphic hardware. Both projects
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developments such as novel algorithms to support logistics operations, novel automation approaches or the design and development of new digital support tools for logistics providers. Significant flexibility
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for the Future of Intelligence (CFI). The candidate will contribute to teaching and lead a research programme in one or more of the following areas: ethical use of machine learning, AI safety, algorithmic
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(Biochemistry, Neuroscience) MSc degree (or equivalent) in Epidemiology, Biostatistics, Data Science or related discipline. Strong quantitative analysis skills and experience developing algorithms and/or
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the coordination of large-scale robot systems (ground and aerial). The ideal candidate will possess hands-on experience with designing and implementing reinforcement learning algorithms, and deploying them onto real
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pivotal role in analysing large-scale genomic and clinical data, applying cutting-edge algorithms, and collaborating with renowned experts in the field. At PBCI, we believe in fostering a collaborative and
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A position exists for a Post Doctoral Research Associate in Department of Applied Mathematics and Theoretical Physics to work on the theory and implementation of algorithms and protocols on quantum
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in our mission to develop clinically useful algorithms, drive high-impact publications, and pave the way for personalised breast cancer treatments. Analyse data from cutting-edge technologies
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animals, while Prof Durbin's works on computational genomics and large scale genome science, including the development of new algorithms and statistical methods to study genome evolution. Moving forward