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approaches that combine artificial intelligence, machine learning, natural language processing, and social sciences. This collaborative and cross-sectoral approach aims to produce robust methods for evaluating
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multidisciplinary team of postdoctoral fellows, PhD and master’s students, and technical staff conducts cutting-edge translational research. We are equipped with state-of-the-art facilities, including a comprehensive
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quantified, and machine learning will be used. Duties As a PhD student, you will work toward a doctoral degree as the final goal, according to the goals specified in the Higher Education Ordinance. In parallel
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persons, including five professors and two postdoctoral researchers. The subject focuses on the development of sustainable materials and production technologies for the construction industry as
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/thesis: Challenges and opportunities with remote sensing and machine learning in forestry Research subject : Soil science Description: WIFORCE Research School Do you want to contribute to the future
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of Informatics (Faculty of Social Sciences), which contributes perspectives on human-computer interaction, information systems, digital practices, and socio-technical change, with a focus on how digital
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EU-MSCA PhD position: Molecularly imprinted polymers for phosphopeptide assays of oncogenic pathways
with us! Here you can learn more about what it's like to work at Malmö University: Work with us We are looking for a Doctoral student student in chemistry This is an exciting opportunity for a highly
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primarily focused on shipping and its conversion to fossil-free, but applications in road transport and work machines are also studied. The work is carried out in close collaboration with other universities
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its supply system, the research is primarily focused on shipping and its conversion to fossil-free, but applications in road transport and work machines are also studied. The work is carried out in
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at the intersection of AI and advanced electron microscopy. The project focuses on developing novel self-supervised and physics-informed deep learning methods to restore and denoise Transmission