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machine learning and AI acceleration. Perform performance, power, and area (PPA) analysis of processor and accelerator designs. Publish research findings in top-tier conferences and journals and contribute
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learning-based model predictive control (MPC) algorithms for multi-agent multirotor drone navigation around vessels in maritime environments. The role will focus on integrating multirotor crash predictions
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and research in several areas. These include, but are not limited to: Adversarial location and network interdiction models Adversarial machine learning attacks and defense (e.g., against Bayesian
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research in formal verification, machine learning and artificial intelligence system assurance. The successful candidate will develop new techniques and tools for analysing, verifying and improving
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Materials Design - Develop and apply machine learning and AI models (e.g., ML interatomic potentials, generative design, reinforcement learning) to predict and design materials. - Perform first-principles and
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research, innovation, and learning for all faculty, staff and students. Our commitment to employment equity helps achieve inclusion and fairness, brings rich diversity to UBC as a workplace, and creates the
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or joint research, in the area of interest of the hosting laboratory (Prof T Carlomagno) Acquire, analyse and interpret data - structural biology, biochemical and biophysical data Acquire, analyse and
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matching, optimal transport or cell-cycle modelling. Key Responsibilities These include but are not limited to: Leading an independent research project in scientific machine learning and mechanistic
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 12 days ago
it, 80 years later. For generations, our people have turned curiosity into ideas that have shaped Australia and our region. Learn more about ANU, our history and the community that has shaped us: ANU
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focused on using spatial profiling and machine learning of human specimens in combination with functional experiments in animal models to understand cancer initiation, progression, and metastasis. We