321 structures-"https:"-"https:"-"https:"-"https:"-"Birmingham-Newman-University" Fellowship positions
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, potentially including novel Josephson junction structures, hybrid superconducting-normal metal devices, materials development, wafer scale production issues and similar. The post is funded by Royal Holloway and
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: Resistance Analysis: Conduct simulations to analyze wave interactions, buoyancy, and stability of modular floating structures. Optimize designs for dynamic environmental conditions (e.g., waves, tides
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projects Knowledge of clinical research structures Experience of interpreting microbiological information for clinical care (culture and sensitivities, serology, point of care tests, etc.) Experience
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project - “Welded/bolted bi-steel joints for marine infrastructure”. Qualifications Applicants should have: (a) a doctoral degree in Structural Engineering and must have no more than five years of post
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, and materials micro-structural analysis (e.g. XRD, SEM, MIP, TGA, and FTIR). Good English writing and communication skills - essential for data analysis and communication with stakeholders Experience in
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postdoctoral fellow to study HIV-1 vaccine immunology. We use an interdisciplinary approach combining structural biology, molecular biology, biochemistry, and immunology to generate insights that can be
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scientist to work in the field of structural characterization of quantum materials using x-ray scattering techniques and structure modeling. Required Qualifications PhD in Physics, Chemistry, or Materials
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excellent experimental skills. Knowledge and hands-on experience in active-doped silica-based fibre fabrication, spectroscopic characterisation of doped fibres, and the construction and testing of fibre
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the construction and testing of fibre lasers and amplifiers would be beneficial for this position. You must have proven skills in the critical evaluation and interpretation of data and of working as
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) [Appointment period: each for twelve months] Duties The appointees will assist the project leader in the research project - “Construction skill transfer learning for smoother worker-robot collaboration in