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, bioRxiv 2026, doi: 10.64898/2026.07.30.741759) for biological systems. You will lead a computational research project extending DMMSs from population-level to single-cell data, combining neural networks
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systems, predictive modeling, or optimization problems related to packaging or mechanical systems. • Background in logistics optimization, supply chain modeling, or distribution network analysis
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Virtual Research Institute (WIB) - Łukasiewicz Research Network - PORT Polish Center for Technology Development, Co-Financed by the Polish Science Fund, project no. WIB-4/2024-O04, entitled “Personalized
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Virtual Research Institute (WIB) - Łukasiewicz Research Network - PORT Polish Center for Technology Development, Co-Financed by the Polish Science Fund, project no. WIB-4/2024-O04, entitled “Personalized
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Qualifications Experience with graph neural networks, machine-learning interatomic potentials, or related scientific machine-learning methods for atomistic systems. Familiarity with uncertainty quantification
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process of continuous germplasm improvement, discovery trait research and methodology optimization to reach greater breeding efficiency. The general research technologies/methodologies and approaches
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this new hybrid network. Your code will directly enable the next generation of energy-efficient AI clusters. Project scope You will bridge the gap between custom optical hardware and standard AI software
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projects focused on optimization, data analytics, and control of power distribution systems. This position offers the opportunity to collaborate closely with utility company partners and national
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 22 days ago
clinicians, academics and health care leaders of the future who work in partnership with their patients and colleagues to provide optimal care for individuals while strengthening the system and society they
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attracting highly qualified talent. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security