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Full time: 35 hours per week Fixed term: for 36 months Posts available: 2 The Opportunity: This project aims to (1) understand the fluid dynamics of small-scale processes in the Arctic Ocean that
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Despite significant advances in numerical techniques and computing hardware, the high computational cost of large-scale 3D computational fluid dynamics (CFD) modelling remains a major challenge. A
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through partnerships with Dell Medical School, the School of Social Work, and many other academic and research units on campus. The campus is situated in Austin, one of the nation’s most dynamic and fastest
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Administration (CADM) is a 5,000+ employee organization that supports the university's overall excellence by understanding and serving the needs of its schools, students, faculty, staff, alumni, and surrounding
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for biomedical applications while working collaboratively within a dynamic and interdisciplinary research environment. This is an excellent opportunity for individuals seeking to expand their technical expertise
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% superannuation & leave loading Location: Kensington, NSW (1 day WFH per week) Benefits: Cultural Leave and Indigenous Employee Network This position is open to Aboriginal and/or Torres Strait Islander applicants
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through cutting-edge research. The Beckman Research Institute of City of Hope invites applications for a talented Postdoctoral Fellow to join our dynamic research team. As a Postdoctoral Fellow, you'll have
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Position Description Laureate Postdoctoral Fellow - Dynamical Systems, UNSW Sydney, Australia The Postdoctoral Fellow will undertake research within a five-year Laureate Fellow project funded by
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environmental research methods is essential. A dynamic and innovative research trajectory. Scholars with expertise in climate and health, environmental toxicology and epidemiology, environmental exposure science
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(including neural quantum states), stabilizer and near-Clifford simulation, Gaussian/free-fermion methods, open-system dynamics (Lindblad master equations). - Machine learning for physical systems: deep