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the Job related to staff position within a Research Infrastructure? No Offer Description Postdoc in Machine Learned Semiconductor Material Properties for Quantum Transport Simulations The simulation
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and Liu, Supervised learning in physical networks: From machine learning to learning machines, PRX 11, 021045 (2021) [2] Stern and Murugan, Learning without neurons in physical systems, Ann Rev Cond
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risk factors. The main objective is to design and apply machine learning and deep learning methods to understand and investigate the functional behavior of gender-specific cancers. The work will include
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background knowledge in statistical genetics, machine learning, omics data analysis, and computational biology. Additional knowledge in transcriptomics, statistics, and foundation models is also desired. Fixed
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-off companies. CONTEXT AND MISSION We are seeking a postdoc to join the Quantum Machine Learning team (QML-CVC) in beautiful Barcelona. The QML-CVC team (https://qml.cvc.uab.es /) is part of
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related to staff position within a Research Infrastructure? No Offer Description ELLIS Institute Finland is a newly established world-class research hub in AI and machine learning – and we are growing! We
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materials and technologies. Using advanced computational modeling and machine learning, we seek to elucidate the mechanisms governing the self-assembly of lignin in different solvents and the formation
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of sea turtles - Developing innovative machine learning methods to analyze the sounds associated with these behaviors - Automating the processing of audio and visual data to optimize the quantity and
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Postdoctoral Researcher Position in Ecological Knowledge-Guided Machine Learning at Aarhus Univer...
quality modelling, with focus on Knowledge-Guided Machine Learning. The position is a rewarding opportunity to be integrated in an excellent freshwater group. The department’s research and advisory
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approaches for using machine learning to analyze X-ray data, particularly Resonant Inelastic X-ray Scattering (RIXS). The position will collaborate with experts in RIXS experiments (Mark Dean), computational