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of computation that aim to lower energy consumption for machine-learning and information processing tasks (see, e.g., arXiv:2308.15905 ). Quantum phenomena in information processing: Investigating how genuine
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Full Time Posting Number 25FA1242 Posting Open Date 12/15/2025 Posting Close Date Qualifications Minimum Education and Experience This position requires a PhD in Electrical and Computer Engineering or a
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Mattelaer, Christophe Ringeval). Research activities in include SM and BSM aspects of collider physics (LHC and future colliders, simulation tools, machine learning, effective field theories, amplitude
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omics and big-data sets using statistical and machine learning approaches. The details on responsibilities, obligations and rights of the position see: https://www.osi.lv/en/vacancies/ Provisional start
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Position as Computational Analyst / Bioinformatician in RNA Therapeutics and Cardiometabolic Disease
PSCSR-seq. Training PhD students and post-docs to analyze large-scale datasets and interpreting results. Provide input to projects in our group and help with illustrating complex biological datasets. Your
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tasks and zero-shot evaluation in linguistic analysis. Profile • Master’s degree (M2) or PhD in computer science, NLP, machine learning, deep learning, or a related field. • Strong experience in machine
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accelerate the global shift to electric mobility. This PhD will build an AI-driven fleet-scheduling framework that learns from battery data in real time and optimises charging, operations and maintenance
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of possible methodological components include self-supervised temporal representation learning for large volumes of unlabeled AE/electrochemical time-series data, switching state-space models that describe
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Leibniz-Institut für Präventionsforschung und Epidemiologie – BIPS GmbH | Bremen, Bremen | Germany | 29 days ago
learning, data science and research data management, and causal inference methods (Iris Pigeot, Marvin Wright, Vanessa Didelez), and etiologic and molecular epidemiology (Konrad Stopsack, Krasimira
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fully funded PhD position within the LowDataML doctoral network, focusing on developing innovative machine-learning approaches for drug discovery under low-data conditions. LowDataML aims to bridge