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an exciting research program to develop next-generation sensor devices and systems for human-machine interactions. Qualifications PhD in Materials Sciences, Robotics, Mechanical Engineering, or related
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dependent upon having been awarded a PhD; if this is not the case, initial appointment will be at Research Assistant Grade 6B (£39,148 - £41,833 per annum including London Allowance) with payment at Grade 7
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point 31-34 which is £ 45,103 - £48,679 per annum inclusive of London Allowance. About you Candidates should either have a PhD or equivalent qualification in Mathematics, Physics, Biophysics, or relevant
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membranes. Please see https://blacklow.hms.harvard.edu/ for additional information on areas of research. We welcome applications from recent PhD graduates who are interested in these or related fields
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Responsibilities: Research and develop novel ML-based methodologies and algorithms in LLM-empowered Sub-Graph Learning for Large Graph Models. Working closely with other Postdoc/RA/PhD students to discuss the ideas
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conferences. • Work with multidisciplinary teams across NUS and external collaborators to validate and apply developed tools. Qualifications Eligibility: • Degree and experience: Applicants must have a PhD in
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 4 days ago
and release profiles. Admission Requirements: Mandatory: - Candidate must have Master's degrees in Pharmacy or Pharmaceutical Sciences; - Candidate must be enrolled in a PhD program preferably in
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working with Prof. George Chen. Join a multi-disciplinary team at the TDHVL that includes academic staff, postdoctoral researchers, engineers, PhD and undergraduate students. For further details on our
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Machine Learning Group, Department of Engineering, CambridgeMLG Cambridge About Us News Research Publications People PhD Admissions Blog Latest News Papers with MLG authors to appear at ICML and
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and PhD students with expertise in nanomaterials, spectroscopy, STEM, and theoretical modelling. Characterization of quantum materials with AFM, XPS, XRD, Raman, PL STEM-HAADF and nanofabrication