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We are seeking a full-time Postdoctoral Research Assistant in Physics-Based Modelling of Advanced Batteries to join the Department of Engineering Science under the supervision of Prof Charles Monroe
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We are seeking a full-time Postdoctoral Research Assistant in Physics-Based Modelling of Advanced Batteries to join the Department of Engineering Science under the supervision of Prof Charles Monroe
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PhD in Inorganic or Materials Chemistry or a relevant subject area, (or be close to completion) prior to taking up the appointment. The research requires experience in synthetic inorganic/materials
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. Qualification requirements The selected candidate should have a master’s degree in a related field: e.g., civil engineering , mechanical engineering , computational materials science , or applied mathematics
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state physics, chemistry and materials science. Demonstrated mastery of diamond anvil cell preparation and sample loading. Experience in synchrotron X-ray diffraction and Raman spectroscopy measurements
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Pregnancy. Current risk-communication materials in maternity care are often text-heavy, numerically dense, and disconnected from the lived experiences of women and families. Building on prior epidemiological
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Applications are invited for a Postdoctoral Research Assistant position with the WISDOM project (mm/sub-mm interferometric studies of molecular gas and supermassive black holes in galaxies near and far; strong gravitational lensing). Under the supervision of Prof. Martin Bureau, the postholder...
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close to completion) in Materials Science, Physics, Chemistry, Nanotechnology, Electrical Engineering, or a closely related field, with a strong background in the synthesis and characterisation of 2D
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Applications are invited for a Postdoctoral Research Assistant position with the WISDOM project (mm/sub-mm interferometric studies of molecular gas and supermassive black holes in galaxies near and far; strong gravitational lensing). Under the supervision of Prof. Martin Bureau, the postholder...
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in computational surface science, electronic structure theory, computational materials discovery, or machine learning in materials science. Research competence and initiative proven through