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vision research. The department fosters interdisciplinary collaboration, addressing real-world challenges through innovative machine learning, data science, and intelligent systems research. About the role
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Travel ” which examines signal processing and machine learning methods for inferring active travel activities from optical fibre signals. About You Applicants must have an Undergraduate Degree in
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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
illnesses. The post holder will also co-supervise a PhD student who will be involved in the same project. This is a highly interdisciplinary project combining forest ecology, remote sensing, machine learning
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learning. The post-holder will be familiar with the use of these techniques and experience of dataset construction and data mining will be essential. The successful applicant will have completed an MPhil/PhD
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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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superconducting qubits and millikelvin electronics Did you recently get your PhD in circuit quantum electrodynamics (cQED) and are now looking into taking the full potential of your skills into use for making new
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this suits a candidate with a background in optical systems / imaging, or with more experience in machine vision, or systems control and automation, or data interpretation. A candidate would not be expected
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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
holder will also co-supervise a PhD student who will be involved in the same project. This is a highly interdisciplinary project combining forest ecology, remote sensing, machine learning, epidemiology
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screening (XChem), PDB deposition and biophysical techniques including SPR, DSF and NMR. Applicants must hold a PhD in Biochemistry/ Biophysics / Chemical Crystallography or a related field (or have submitted
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-quality robotics research in the areas of robot grasping and manipulation, kinematics and mechanisms, sensing, and human-robot interaction. Within CORE, SAIR focuses on multimodal machine learning for human