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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 22 days ago
(bio)physics, statistical mechanics, scientific computing and also a keen interest in interdisciplinary research and collaboration with experimental groups. PhD students hold (or expect to complete soon
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Research Associate specialising in statistical modelling and machine learning to join our multi-university multi-disciplinary team developing a groundbreaking technique based on autofluorescence (AF) imaging
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methodological development and applied work, with expected contributions to scientific publications and participation in collaborative meetings with the partner institutions. PhD in AI or statistics, machine
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University of Helsinki, Department of Mathematics and Statistics Position ID: 568 -POST_MATHPHY [#26742] Position Title: Position Type: Postdoctoral Position Location: Helsinki, Southern Finland
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) information-theoretic active learning, and c) capturing uncertainty in deep learning models (including large language models). The successful postholder will hold or be close to the completion of a PhD/DPhil in
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. About You The successful applicant will have, or soon obtain, a PhD degree in mathematics or related, or equivalent level of professional qualifications and experience, with expertise in at least one of
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presentation at conferences and manuscript preparation Specific criteria include: Recent MD or PhD (0 - 3 years) in a relevant biological science or bioengineering discipline Strong critical thinking skills
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Essential Qualifications Applicants require a PhD in a Biochemistry-related field Preferred Qualifications: Experience with animal behavioral studies, advanced statistics, and experimenta design
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. This may include lecturing, small group teaching, and tutoring of undergraduates and graduate students. Applicants should hold a PhD/DPhil, (or close to completion) in atmospheric physics or related fields
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also have or be close to completing a PhD in any of the following areas as well as the will and commitment to learn relevant topics from the other areas: Statistical and machine learning, mathematical