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Artificial Intelligence and assistive technology, we aim to be at the forefront of equipping key stakeholders to identify, explore, and scaffold opportunities for strengths-based approaches that allow
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system with integrated sensors. You should hold or be near completion of a PhD/DPhil with relevant experience in the field of robotics, biomedical engineering, information engineering, electrical
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from Theoretical Computer Science. The group is located jointly at the Faculty of Physics – as part of the Quantum Optics, Quantum Nanophysics, and Quantum Information Group – and at the Faculty
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the spectrum of Mathematical Sciences. It is part of the Faculty of Science and Engineering, which comprises five schools and two institutes. This position is based in the Centre for Data Science, Statistics and
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through high-quality publications. Desirable Criteria: 13. A PhD (or be close to submission) in Electrical Engineering, Energy Systems, Control Engineering, Computer Science, Artificial Intelligence, or a
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in the ongoing drive to reduce animal use in scientific research. Applicants must hold a PhD in Cell Biology or related discipline and have a track-record of success, as indicated by first-author
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encouraging of collaborative interactions between groups. Role Summary Applicants will have a PhD in Biochemistry, Protein Engineering, Structural Biology or Synthetic Biology, Molecular Plant Pathology
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://degradationproject.com/ ) and NEXGENNa (http://nexgenna.org/ ) projects and participation in regular relevant FI meetings. Applicants should hold (or be about to obtain) a PhD in Chemistry, Materials Science, or a closely
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://degradationproject.com/ ) and NEXGENNa (http://nexgenna.org/ ) projects and participation in regular relevant FI meetings. Applicants should hold (or be about to obtain) a PhD in Chemistry, Materials Science, or a closely
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Engineering, Mathematics, Statistics, Computer Science or conjugate subject; strong record of publication in the relevant literature; good knowledge of machine learning algorithms and/or statistical methods