13 computer-science-intern-"https:"-"https:"-"https:"-"https:"-"CUBO" positions at University of Copenhagen
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are interdisciplinary, building on international and national collaborations. With a platform in medicinal chemistry, our projects bridges with molecular pharmacology, computational and biostructural chemistry. The lab
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customized software tools and interfaces tailored to the group’s evolving research needs, focusing on efficiency and user experience. We expect A BSc degree or MSc in Computer Science (correlation with
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Department of Clinical Medicine Faculty of Health and Medical Sciences University of Copenhagen The University seeks to appoint a clinical professor of Internal medicine: Endocrinology with special
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flexibility and accuracy. Further, you must have good interpersonal skills and interest in working in an international team. Knowledge of cell biology, stem cell biology or developmental biology is an advantage
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Medical Sciences (SUND), please seehttp://www.pharmacy.ku.dk and https://sund.ku.dk Foreign applicants may find this link useful: https://www.ism.ku.dk (International Staff Mobility). Application
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external events Research at MOBILE is primarily interdisciplinary. Therefore, familiarity with or interest in law, political science, sociology, data science, or related fields is an advantage. Work
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to an innovative research program at the intersection of psychotherapy research and psychedelic science. Copenhagen University Clinic for Psychedelic Research (NOESIS): NOESIS is a research clinic at the Department
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Faculty of Health and Medical Sciences University of Copenhagen The University seeks to appoint a clinical professor of Internal medicine: Endocrinology with special focus on diabetes precision medicine and
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the Center for Core Facilities at the Faculty of Health and Medical Sciences, University of Copenhagen, which brings together the faculty’s strategic research infrastructures. The purpose is to strengthen
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Department of Public Health. The group works at the intersection of computer science, mathematics, biology, and epidemiology, developing and applying novel statistical methods and deep learning approaches