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physics, with expertise spanning both observational studies and theoretical or computational modeling. It offers an international and collaborative work environment that values equality, diversity
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follow the 3-step application process here . Application dates for the commencement of the Integrated PhD program in January/February 2026: Round opens: 1 July 2025 Closing date: 31 August 2025 About
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For further information about the structure and rules of the PhD programme, please contact the PhD Administration email: phd@hrsc.ku.dk Information about the recruitment process is available from HR South
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The National Industry PhD Program is an Australian Government initiative to enhance workforce mobility among graduate researchers, and to promote knowledge transfer between academia and industries
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Research Assistant/Associate in Photonics Integration of Graphene and Related Materials (Fixed Term)
optoelectronics, light emission, optical sensing and quantum communications. This is an ambitious research program, with a strong interdisciplinary nature, across photonics, plasmonics, device physics, electrical
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Computational verification of high-speed multi-material flows, where physical experimentation is highly limited, is seen as critical by the defence Sector (source: the UK Atomic Weapons
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background and an interest and expertise in physical, computational and/or analytical chemistry. Please note that this is a 4-year Graduate Teaching Assistant (GTA) studentship, with a slightly higher teaching
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, but it would be possible for those with mathematics, physics or other computational training to learn the healthcare context Experience in one or more of the following would be desirable: Programming in
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. The way we process data produced by computational nodes is therefore constantly evolving. While historically, mainframes provided heavy lifting for dumb end user terminals, computing capabilities now
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Development of novel processing techniques Modelling techniques that can inform the direction of experimental activity Physical, mechanical and materials characterisation techniques Data-driven approaches