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: Investigate and design optimal computing and communication architectures for hardware acceleration of large-scale machine learning workloads Perform characterization and modeling of electronic and optical
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Subject area: Drug Discovery, Laboratory Automation, Machine Learning Overview: This 36-month PhD studentship will contribute to cutting-edge advancements in automated drug discovery through
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” research themes. The successful candidate will have: a PhD in Translation Studies/Machine Translation; practical experience conducting data-driven research in a machine translation/large language models (LLM
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, biodiversity monitoring, and climate resilience. The work supports strategic priorities in Environmental Sciences, Software/Cyber. PhD researchers will explore how AI-driven Earth observation, computer vision
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is made for you! Information We invite highly motivated students with a strong background in mathematical control theory, and a keen interest in machine learning to apply for the PhD position within
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computational sub-team that includes computer scientists and computational PhD students, fostering an interactive environment of technical exchange, code review, mutual support, and collaborative problem-solving
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This PhD explores light estimation and synthetic relighting of real scenes by combining generative deep learning with computer graphics. It aims to reduce issues such as hallucinations and temporal
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | 6 days ago
Understanding (CASUS) is a German-Polish research center for data-intensive digital systems research. The Department of AI4Quantum – Machine Learning for Quantum Simulation and Computing is looking for a PhD
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descriptors to support machine learning model development to accelerate materials discovery: Perform high-throughput DFT and molecular dynamics simulations to investigate the thermodynamic, structural, and
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descriptors, molecular simulations, and machine learning, this PhD project seeks to predict ion-exchange isotherm parameters directly from molecular properties. These predictions will be integrated