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Field
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highly motivated and technically proficient Research Fellow in Control and Embedded Systems Engineering to support the development and deployment of intelligent, safety-enhanced BMS technologies within a
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will develop autonomous on-board guidance algorithms for space missions using open-source numerical solvers for convex optimisation developed at the University of Oxford. The focus will be on designing
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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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an exciting opportunity to a graduate with the relevant skills and knowledge to develop and implement machine learning techniques to derive new-to-sector advanced insights from Aids to Navigation maintenance
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. The post is funded by NIHR Oxford BRC and is fixed-term for 12 months in the first instance. About The Role The ideal candidates will have experience in developing, implementing, and evaluating healthcare
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of algorithms for automatic analysis of data received at the backend. About You You should hold a MSC degree in a relevant field, and have experience of web development, SQL or NoSQL database management systems
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Job Purpose To make a leading contribution to the development of innovative muon tracking algorithms for cutting-edge applied nuclear physics research. The successful candidate will be expected
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web technologies Experience in teaching bioinformatics Previous experience with AI and/or machine learning approaches Interest in reproductive health and/or development of clinical tools and algorithms
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. This role will involve developing and applying analysis plans using a variety of advanced methods with the support of project supervisors. The postholder will have completed a PhD in a relevant discipline and
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mobile robotics, you will manage own academic research and administrative activities, adapt existing and develop new methodologies in robotics, design working algorithms from theories, deploy and test