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Field
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neurocritical care research The Opportunity We are seeking a Research Fellow - Data Science professional with strong expertise in machine learning, deep learning and high-frequency physiological signal analysis
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, alignment, and characterisation of laser-based instrumentation. • Strong experience with computer programming, both for signal processing and experimental hardware control (e.g., C, C++, Python, MATLAB
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operations. These research opportunities include ongoing efforts to identify and treat traumatic brain and neurosensory system injuries as well as to understand and mitigate the deleterious effects of repeated
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communication skills Commitment to mentoring graduate and undergraduate students Desirable (but not required): Experience with time-series QA datasets (e.g., Time-MQA, TSQA, MTBench) Background in signal processing
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This is a theoretical/computational postdoctoral position for the prediction and development of point defects in two-dimensional materials for applications in quantum technologies. Project
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in application-based computational biology, including single-cell sequencing techniques. Strong experience in deep learning and AI. Structural biology experience is a strong plus point. Pragmatic and
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have a postgraduate degree, ideally a doctoral degree, in a relevant field and experience in computer-based analyses and presentation of experimental data. The successful applicant would have a proven
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Australian National University | Canberra, Australian Capital Territory | Australia | about 1 month ago
, and Myanmar. The Research Fellow will serve as the key point of contact with our research partners and will be responsible for project management across several workstreams, while also contributing
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This is a theoretical/computational postdoctoral position for the prediction and development of point defects in two-dimensional materials for applications in quantum technologies. Project
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academics, visiting fellows, and librarians. In this role you will be fully integrated into the RAI community. Application process Applications for this vacancy are to be made online via www.recruit.ox.ac.uk