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they learn, PRL134, 147402 (2025). Qualifications We seek candidates with: A PhD in physics, applied mathematics, materials science, mechanical engineering, computer science, or a related field. Strong
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. The successful candidate will have the responsibility of developing, in collaboration with Dr Whelan and the PhD students, machine learning tools for the handling of the Mauve and MUSE datasets. They will also be
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to apply Website https://www.academictransfer.com/en/jobs/359291/postdoc-in-machine-learning-and… Requirements Specific Requirements We will base our selection on the following components: a PhD degree in an
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 9 days ago
skills Specific Requirements The candidate must hold a PhD in machine learning and have strong mathematical skills. Knowledge of bandit models is a plus. LanguagesFRENCHLevelBasic LanguagesENGLISHLevelGood
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additives, electrochemical evaluation, and mechanistic studies to advance the fundamental understanding and industrial scalability of CO2-to-methane conversion. Where to apply Website https
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transformation of society in western Europe (GREEKWEST)', which is funded by an ERC Starting Grant and hosted in the Department of Archaeology, Classics and Egyptology ( https://www.liverpool.ac.uk/archaeology
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automated configuration mechanisms based on fingerprinting and machine learning to ensure traffic analysis remains faithful to the behavior of the monitored machines. Finally, you will validate your solutions
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. Where to apply E-mail lorraine.dubuis@unige.ch Requirements Research FieldPsychological sciencesEducation LevelPhD or equivalent Skills/Qualifications Desired profile: PhD in psychology, neuroscience
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. Requirements: PhD completed less than 7 years ago in Computer Science or related areas; experience in machine learning and data science (supervised/unsupervised models, recommendation and evaluation/robustness
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den öffentlichen Dienst) salary group 14 TV-L. This post is linked to the possibility of habilitation on Magnetic Materials or Magnetic Domains. Where to apply E-mail jmc@tf.uni-kiel.de Requirements