28 algorithm-development-"Helmholtz-Zentrum-Geesthacht" positions at Linköping University
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address outstanding questions on behavioural evolution in canids. Your work assignments Understanding how behaviours evolve is a long-standing goal in evolutionary biology. Using the domestic dog as a model
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The Division of Biology at Linköping University invites applications for a four-year PhD to address outstanding questions on behavioural evolution in canids. Your work assignments Understanding how
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mathematics. The applicant should be skilled at implementing new models and algorithms in a suitable software environment, with documented experience. Experience in applying or developing machine learning
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prominent approach to AI, with impressive performance in many application domains, including materials discovery. This development has a huge potential for societal impact, with applications in renewable
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, localization, and sensing, with a focus on developing next-generation multiple-antenna systems while optimizing overall system performance. As a doctoral student, you devote most of your time to doctoral studies
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with machine learning and generative AI algorithms, with working knowledge of deep learning frameworks such as PyTorch or TensorFlow is considered a strong advantage. • Extensive experience in multi
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, and includes responsibility for developing the department’s environmental research lab. You will collaborate across disciplines, develop methods aligned with strategic goals, and contribute to seminars
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skills are integrated in the development of professional and interprofessional identities, and how these are expressed in the daily health care work. Research in medical education also includes interactive
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application! Work assignments The purpose of the position as an assistant professor is that the teacher should be given the opportunity to develop his independence as a researcher and to merit both
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Pharmacology (KKF). The overall aim of the project is to develop improved diagnostic and predictive tools for hematology and clinical immunology. The project is a collaboration with Sofia Nyström ’s group