76 machine-learning-"https:" "https:" "https:" "https:" Postdoctoral research jobs in Sweden
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application! We are now looking to appoint a postdoc in the field of AI and machine learning with a focus on scientific applications. Work assignments The primary focus of the postdoc positions is research in
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higher education teaching and learning. The purpose of the position is to develop the independence as a researcher and to create the opportunity of further development. The research tasks include
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support, among other benefits. See more information at: https://www.umu.se/en/department-of-computing-science/. You will research in collaboration with the Associate Professor Zoe Falomir. Interested
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related fields. Experience in Machine Learning/AI, mathematical, computational and statistical training are also advantageous. About the employment The employment is a temporary position of two years
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University | Lund University. Ready to shape the future of research? Find more reasons why Lund University and the HT Faculties is right for you here , and learn more about Working in Lund , Moving to Lund
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and refined our pioneering AI-driven methods. This project focuses on improving protein structure prediction, design, quality assessment, and dynamics using innovative machine learning techniques. You
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mathematics, data science and machine learning for image recognition. Moreover, you will develop methods and software that will allow new characterization of nanoscale materials. Therefore, your research will
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presentation of analysis results. The ability to work with large and complex datasets. Excellent spoken and written English skills. Experience in machine learning, predictive modeling, and/or Bayesian methods
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technology. We are located on LTH's campus in northern Lund. At the Division of Electromagnetics and Nanoelectronics within the Department, we develop and study new generations of electronics based on advanced
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the Division of Data Science and Artificial Intelligence and the employment is with Chalmers University of Technology. The division’s research spans from foundational machine learning theory to applications