43 postdoctoral-position-in-material-science PhD scholarships at Karolinska Institutet
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has 12 research groups, about 115 research students and about 140 employees. The doctoral position is placed within the IMPAQT (Implementation and Quality) research group. Our aim is to generate
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of four years of full-time doctoral education is required. The research group Our research group operates within the Division of Clinical Chemistry at the Department of Laboratory Medicine. Our primary
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an optimal place to grow and drive outstandingly important research with both short- and long-term clinical impact. The doctoral student project and the duties of the doctoral student You will get a pioneering
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of four years of full-time doctoral education is required. The Department of Medical Epidemiology and Biostatistics (MEB) conducts research in epidemiology, biostatistics and health economics across a broad
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to discuss science and problem-solving. The student will take part in these meetings and present data twice per semester. What do we offer? A creative and inspiring environment full of expertise and curiosity
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biomedical science. The department is among the largest of its type in Europe and has especially strong research profiles in psychiatric, cancer, reproductive, pediatric, pharmaco, genetic, and geriatric
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should hold a masters' degree (or equivalent) in molecular biology, biotechnology or another relevant life science or related fields. We place great emphasis on personal suitability. To succeed as a PhD
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requirements for doctoral education In order to participate in the selection for a doctoral position, you must meet the following general (A) and specific (B) eligibility requirements at latest by
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of four years of full-time doctoral education is required. The Department of Microbiology, Tumor and Cell Biology (MTC) at Karolinska Institutet conducts research and teaching within immunology, infection
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position as PhD student in data-driven life science. Data-driven precision medicine and diagnostics covers data integration, analysis, visualization, and data interpretation for patient stratification