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application! We are looking for a PhD student in automatic control at the Department for Electrical Engineering (ISY). Your work assignments The advertised positions will be within the Competence Center SEDDIT
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for efficient last-mile deliveries with a focus on climate and flexibility. Using advanced modeling and data analysis, you’ll create solutions that make final deliveries smarter and more sustainable. Your work
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application! We are now looking for a PhD student in Integrated Circuits and Systems, at the Department of Electrical Engineering (ISY). Your work assignments The objectives for this position are to develop
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application! We are looking for a PhD student in Medical Science Your work assignments The project investigates how grief is processed in the brain, how self-related behaviors are affected during periods
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. Your work assignments The overall aim of the project is to investigate how firms can leverage specialised AI models to develop innovative offerings, business models, and ecosystem collaborations. While
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application! We are looking for a PhD student in Medical Science Your work assignments As a PhD student, you devote most of your time to doctoral studies and the research projects of which you are part. Your
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application! We are looking for a PhD student in Medical Science Your work assignments As a PhD student, you devote most of your time to doctoral studies and the research projects of which you are part. Your
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application! We are looking for a PhD student in Medical Science, as part of the larger EU Marie Curie MCSA Doctoral Network STEM-CORE. Are you passionate about working with stem cells or stem cell-based
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at the Department of Science and Technology, Campus Norrköping. As a doctoral student, you will take part in a project exploring how AI can create engaging and interactive educational environments. You will
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application! We are looking for a PhD student in biomedical engineering with a focus on deep learning for medical images Your work assignments The position focuses on developing methods for federated learning