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Field
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The Data-Driven Mechanics Laboratory is seeking a highly motivated doctoral student to study physics- and thermodynamics-informed machine learning (ML) for the mechanics of material failure
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Full Announcement and Application at https://www.jobbnorge.no/en/available-jobs/job/260803/phd-fellow-in-knowledge-driven-machine-learning The positionJoin Integreat, a Norwegian centre of excellence
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Scholarship for the PhD in Medical Sciences in the field of Sleep Science and Neuroscience for thePhD Research Project ‘PHD-2023-3: Development of a Machine Learning-based nightmare detection method
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Job description:Title: DC13, PhD fellowship in explainable machine learning techniques to support the design of plant-based fermented food products – Development of a serious game to support the
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scattering and runs a specialized subgroup on machine learning (artificial intelligence and deep learning) for the analysis and prediction of experimental scattering data. Currently, there are several options
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independent researcher, including through grant writing, independent papers, consulting, trainings. The skills, qualifications and experience required to perform the role are: PhD in Machine Learning, Climate
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relevant field such as NLP, Information Retrieval, Artificial Intelligence or Machine Learning and be able to demonstrate a strong track record of independent research and high-quality publications
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. Knowledge and experience in data science and machine learning is particularly beneficial. Excellent communication and interpersonal skills are essential, along with intellectual independence and a willingness
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neuroscience, computational cognitive science, physics, mathematics, computer science, machine learning, engineering or a related field. Preference will be given to candidates with: previous experience in
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; experience in programming, data management and interpretation; comfortable developing data-driven and machine learning approaches from experimental data; ideally has experience in blast engineering, or damage