277 machine-learning "https:" "https:" "https:" "https:" "https:" "University of St" "St" "St" Postdoctoral research jobs in Sweden
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for a postdoc to join our team at the Division of Systems and Control, Department of Electrical Engineering. Become part of our innovative group and contribute to exciting research in learning-based
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to contribute to a positive work environment. We also value the ability to work independently in carrying out work tasks, as well as openness to learning new skills and taking on new responsibilities. We value
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The applicant must: hold a PhD in a relevant field (e.g. computer science, artificial intelligence, machine learning, computer vision, animal science, biology, veterinary medicine, or a related discipline) have
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: Applied mathematics; Machine Learning; Mathematical Modelling Appl Deadline: 2026/03/24 10:59 PM UnitedKingdomTime (posted 2026/03/18 04:00 AM UnitedKingdomTime, listed until 2026/04/01 04:59 AM
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learning-based control within a collaborative and dynamic environment. About us At the department of Electrical Engineering research and education are performed in the areas of Communications, Antennas and
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. The project focuses on developing an integrated approach that combines machine learning techniques with physics-based models to estimate the health of various system components. The aim is that fault diagnosis
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will also have good opportunities to learn from and socialize with other postdoctoral fellows at the department. For more information about the department: https://www.slu.se/en/about-slu/organisation
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trade union organizations, military service, or other similar circumstances, as well as clinical service or other service/assignments relevant to the subject area. About us The Swedish University
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Join us at the forefront of life science AI. We are looking for a postdoctoral researcher to develop cutting‑edge, multimodal transformer‑based deep learning methods to extract insight from genomic
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, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses