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—an ambitious, EPSRC-funded initiative led by Dr. Sina Sareh, Academic Leader in Robotics. We are looking for a highly skilled researcher with expertise in robotics, AI, software engineering, or computer science
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computational workflows on a high-performance cluster. You will test hypotheses using data from multiple sources, refining your approach as needed. The role also involves close collaboration with colleagues
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of experimental demonstrators. Education, Qualifications and Experience Essential Criteria Applicants should hold a PhD in Physics or a relevant area of electrical engineering. (Applicants should have submitted
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, state-of-the-art laboratories, high-performance computing, and industry collaboration through the London Institute for Healthcare Engineering. About the role We are looking for a highly motivated
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learning, at the intersection of reinforcement learning, deep learning and computer vision, in order to train effective robotic agents in simulation. You should hold a relevant PhD/DPhil (or near completion
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collection and analysis, and co-authoring outputs for academic and practitioner audiences. You will have: (A = Assessed at the Application stage / I = Assessed at the Interview stage) A PhD in (Secondary
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Machine Learning, Statistics, Computer Science or closely related discipline. They will demonstrate an ability to publish, including the ability to produce high-quality academic writing. They will have the
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highlights the urgent need for novel approaches. Antimicrobial peptides (AMPs) are an emergent technology platform which are cost-effective to manufacture and have potential to control wound infection. Despite
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departments: Cardiovascular Imaging, Cancer Imaging, Early Life Imaging, Imaging Chemistry & Biology, Biomedical Computing, Surgical & Interventional Engineering, Imaging Physics & Engineering and Digital Twins
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We are seeking a full-time Postdoctoral Research Assistant to join the Translational Bioelectronics group, led by Prof Tim Denison, at the Department of Engineering Science (Old Road Campus Research