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is, however, the transportation and storage. Current methods rely on liquid compressed hydrogen, which requires high pressures or low temperatures. This project will computationally explore catalyst
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learning, bioinformatics or advanced statistical methods, to help explore molecular, imaging, clinical and/or epidemiological data. You will apply, adapt and develop machine learning approaches to provide
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disease. We are using high-throughput confocal microscopy and proximity labelling and sequencing approaches to characterize molecular regulation in inflammation. The project aims to characterize the role
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of these cutting-edge research projects and in the societal transformation that they entail. We offer a broad range of courses and study programmes to match the skills in demand. We hope that you will help us to
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our research team for addressing a timely societally relevant problem. Project overview The aim is to unravel the mechanisms, and time scales involved at particle scale, for the formation and failure
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extent provide scope for qualifications in research, and the main task is to conduct research of high quality. The research will result in national and international publications. The Assistant Professor
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community, participate in the division's activities such as seminars and workshops, participate in research projects, communicate results through academic publications and help attract external research
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international projects. Our colleagues may be next door, in Helsinki, or in Lisbon, and a lot of our work happens asynchronously over chat or e-mail, but video meetings are also common. We’re a small team and
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We are looking for an up-and-coming researcher who wants to conduct pioneering research to take up a position as assistant professor (associate senior lecturer) in Informatics with a focus on AI and
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application! We are looking for a PhD student in Medical Science. Your work assignments As a PhD student, you will participate in the project: Predictive markers for chemotherapy-induced toxicity in childhood