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Luleå University of Technology is in strong growth with world-leading competence in several research areas. We shape the future through innovative education and ground-breaking research results, and
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if there are special grounds, for example, different types of statutory leave of absence. Applicants who are close to finishing a PhD are also encouraged to apply. Further information The position is fully funded by
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/councils, EU framework program or industry. Qualifications To be eligible for this postdoctoral position, you must hold a PhD in Structural Engineering, Civil Engineering, or a closely related field, with a
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Qualifications: PhD in a relevant field (physics, chemistry, environmental science or related disciplines) or equivalent Knowledge and practical experience in XAFS spectroscopy methodology (sample preparation and
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within the Data Science & AI division (DSAI). With 30+ nationalities and strong industry/academic ties, we offer a dynamic, collaborative ecosystem. The AI and Machine Learning in the Natural Sciences
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forests and marine environment and pest surveillance in aquafarming. Our group will comprise a handful of PhD candidates, and several researchers and MSc students and also a broad interdisciplinary network
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to the future development of research and education. A demonstrated commitment and ability to pursue an academic career is also valued. We are looking for a candidate with a PhD in a social science discipline
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-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven models for complex data, including high
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shape the future of sustainable agriculture. Qualifications The applicant should have a PhD and strong scientific background in (electrical, mechanical) engineering, bioelectronics, physics, neuroscience
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affiliated with both the Faculty of Engineering (LTH) and the Faculty of Science at Lund University. Within CVML there are several PhD-level researchers as well as approximately 20 doctoral students. Research