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Researcher (R3) Country Australia Application Deadline 1 Nov 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
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. Your expertise includes machine learning techniques such as Bayesian optimisation, and you’re comfortable working with experimental data, high-performance computing environments, and (ideally) thin film
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. This collaborative initiative between Monash University’s SensiLab and RMIT University’s Tectonic Formation Lab aims to develop new design methodologies that control the spontaneous dynamics of emergent systems with
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, with a specific focus on complex biological systems. The project aims to apply highly controlled optical trapping techniques to investigate cell–fluid interactions during macropinocytosis (“cell drinking
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Apply now Job no:501477 Work type:Full time Location:Hobart Categories:Research Focused Join a dynamic national team working to improve soil-borne disease management Develop research capacity
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5x Full-time or Part-Time, 12-month, fixed-term opportunities (with possible extension) Exciting opportunity to join a dynamic research team working on melanoma and skin cancer research with a
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including quantum and frequency metrology, quantum gravity and field, quantum information and computation, spintronics and magnetisation dynamics, terahertz and optical technology, as well as bio and medical
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:00 (UTC) Type of Contract To be defined Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a
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leads in research areas including quantum and frequency metrology, quantum gravity and field, quantum information and computation, spintronics and magnetisation dynamics, terahertz and optical technology
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 28 days ago
research challenges in: dynamical systems differential games optimal control numerical optimisation and/or machine learning in control About the opportunity The successful applicant will become part of a