470 computational-physics "https:" "https:" "https:" "https:" "Trinity College, Dublin" Postdoctoral positions in United Kingdom
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experience, with expertise in at least one of the areas: graph polynomials and partition functions, computational counting algorithms and complexity, combinatorics, models in statistical physics. About the
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actively work to ensure our community’s diversity and inclusiveness. This is why we warmly encourage qualified candidates from all backgrounds to join our community. At the Department of Applied Physics, our
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internationally leading programme of research. You should possess significant knowledge in physical acoustics in the ultrasonic regime, cavitation physics, the design and construction of high-powered ultrasound
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An exciting opportunity has arisen for a Postdoctoral Research Assistant in the Department of Physics. Machine learning has made enormous progress during recent years, entering almost all spheres
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within a collaborative and interdisciplinary team of postdocs and PhD researchers in QMUL’s School of Physical and Chemical Sciences, the successful candidate will contribute to both the scientific and
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, Strengthening Communities: Safer Lives (SFSC:SL) parenting programme for the parents of young people at risk of offending or youth violence. The study is an efficacy Randomised Controlled Trial (RCT) being
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on Digesting Science, co-designing a schools programme with drama practitioners, teachers, children and families affected by Multiple Sclerosis, developing and testing participatory activities, prototypes and
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instance), working full-time for 37.5 hours per week, though where possible, part-time arrangements may be considered. About You With a background in materials science, physics, engineering, computer
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fields of research. They will be pursuing an independent programme of advanced study and research in Israel Studies, prepare research publications and publish high-quality research in peer-reviewed
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Computer Science, Chemistry, Chemical Engineering, Physics, or Materials Science. You will develop optimisation and machine-learning algorithms for human- and literature-informed discovery of new materials