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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 23 days ago
will work Christopher Knittel (Sloan School of Management and CEEPR). The project will develop empirical models of supply, demand, and international trade conditions for minerals required for the energy
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utilised by RMIT staff and students globally. The incumbent is expected to rapidly gain expertise in the Campus Solutions platform, Peoplecode scripting, the SAMS data model, and RMIT's customisations
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infection. We focus on defining host pathways that can be therapeutically leveraged to target the HIV reservoir. Our work integrates molecular virology, primary human cell systems, and in vivo models. We
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Workplace Type: On Site Required Sponsorship Eligibility: Not eligible for visa sponsorship Pay Band: 06 Salary: Salary commensurate with education and experience Criminal Background Check: Yes About the
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modeling. Positions may begin as soon as September 2025 . A Ph.D. in Mechanical and Aerospace Engineering, Civil and Environmental Engineering, Atmospheric and Oceanic Sciences, Geosciences, Computational
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Research Associate to join a research team advancing the modelling, control, and real‑time validation of power‑electronics‑dominated power systems. This role supports the ARC Discovery Project “Making weak
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-edge genome engineering tools and in vivo disease models to address fundamental and translational questions in disease biology. Opportunities for cross-disciplinary collaboration with leading experts in
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Science Foundation-funded collaborative research grant focused on understanding and using Paleozoic echinoderms as a model system to explore evolutionary modes. As part of this project, the UMMP is
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LES resolved wake dynamics and the coupling to aero-elastic models and wind turbine control. You will be a member of the Fluid and Offshore Mechanics section, which has a strong track record in offshore
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uncertainty, including the interaction between assets, markets, grids, and policy constraints Stochastic optimisation and dynamic decision models for operational strategies (e.g., maintenance planning, market