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to gain academic research experience and to learn from leading academics. The ideal candidate for this role will have a background in qualitative social science research, such as literature reviews, surveys
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sciences, AI, machine learning or related fields. Strong background and track record in the development of geospatial foundation models from multi-modal Earth Observations is essential as well as strong
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vision systems addressing an urgent industrial challenge with immediate, large-scale impact. The project will take existing knowledge in computer vision and deep learning and apply it directly to a
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thrusts within the lab’s multi-agent security programme. You should possess a completed PhD/DPhil (or thesis submitted by the start date) in Computer Science, Machine Learning, AI, Security, Robotics
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of subjects such as computer vision, Machine Learning, Artificial Intelligence and Kinematics and dynamics. Autonomous systems, Robotics and Automation. Industry 4.0 and Internet-of-Things. Advantageous to have
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the area of quantum machine learning. You will engage in advanced study and academic research, working to develop and carry out research projects, teach and co-supervise graduate students, and contribute
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basic experience in machine learning or computer vision libraries; familiarity with Vision-Language Models (e.g., CLIP, BLIP) or scene-graph inference is a plus. Key Competencies Strong software
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productivity and output • Learn and be fully independent on the existing laboratory workflows, such as transcriptomics analytical pipelines running on Python such as Topometry • Manage own academic
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CFD, thermofluids and machine learning. Experience in Python (or another language), machine learning frameworks, or CFD tools such as OpenFOAM is beneficial but not required. Applicants should hold (or
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contributory pension scheme 38 days annual leave A comprehensive range of childcare services Family leave schemes Cycle and electric car loan schemes Employee Assistance Programme Membership to a variety of