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trigger reconstruction architectures for future particle collider experiments, based on deep learning models distributed across multiple hardware processing stages. The mission of this position, based
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Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job The individual will perform multi-dimensional physiological and biomarker analyses collected from multiple datasets from
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for biomolecular systems, including prediction of protein-ligand, protein-protein, and antibody-antigen structures and affinities, and protein conformational ensembles. Design active learning algorithms and
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for machine learning, with research topics ranging from decentralized and federated optimization, adaptive stochastic algorithms, and generalization in deep learning, to robustness, privacy, and security
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for machine learning, with research topics ranging from decentralized and federated optimization, adaptive stochastic algorithms, and generalization in deep learning, to robustness, privacy, and security
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, the ML Engineer hired for this position will work with Benjamin Gyori at Khoury College and Ayan Paul at EAI and is expected to develop AI algorithms for LLM based RAG systems, work with graduate students
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at the University of Sydney and externally across multiple institutions publish research papers on mathematical theory and the development and analysis of algorithms compile data sets relevant to research in
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research that covers the energy value chain from generation to innovative end-use solutions, motivated by industrialisation and deployment. ERI@N has multiple Interdisciplinary Research Programmes which
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algorithms. Excellent computer skills, including thorough familiarity with multiple programming languages, some experience in writing non-trivial programs, and familiarity with common algorithms, mathematical
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management system for the e-vessel microgrid for coordinated control of multiple energy sources considering cost, carbon, and operation constraints. Operate the simulated electrical model on a real-time system