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performance. The developed methods and algorithms will be validated on both scaled in-house test setups and Å Energi’s pilot HEPs, in collaboration with Volue Industrial IoT AS. Active collaboration with other
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data to assess fault impacts on efficiency and to forecast system performance. The developed methods and algorithms will be validated on both scaled in-house test setups and Å Energi’s pilot HEPs, in
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, harmfulness, jailbreaking, and power-seeking behaviours. You will work alongside Dr Nicola Paoletti and a core team that includes a PhD student from Dr Paoletti’s lab, Prof Osvaldo Simeone from the Department
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, harmfulness, jailbreaking, and power-seeking behaviours. You will work alongside Dr Nicola Paoletti and a core team that includes a PhD student from Dr Paoletti’s lab, Prof Osvaldo Simeone from the Department
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recommendation mechanisms based on semantic analysis and natural language processing, with the aim of facilitating collaboration and convergence of proposals. Developing and training NLP algorithms in multiple
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Australian National University | Canberra, Australian Capital Territory | Australia | about 2 months ago
to: Conduct cutting edge research in machine learning, AI and algorithms, such as but not limited to Bayesian machine learning, human-centered AI and interpretable machine learning, attention markets, gig
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artificial intelligence-based algorithms to optimise operation and predict anomalies in water distribution networks. The algorithms developed should identify patterns and anomalies that indicate the presence
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postdoctoral position is available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research at the intersection of Geometry
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Dr. Darius Bunandar, the Boston University team is led by Prof. Ajay Joshi, and the Harvard University team is led by Prof. Vijay Janapa Reddi. Role Our team has two postdoctoral researcher openings
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. Given their importance, continuous monitoring and fault diagnostics are crucial—especially as machine learning algorithms play an increasingly prominent role in predictive maintenance and reliability