175 application-forms-"https:"-"https:"-"UCL"-"UCL" Postdoctoral positions in Denmark
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The Department of Ecoscience at Aarhus University invites applications for two postdoctoral positions to strengthen our research on image recognition, computer vision and deep learning applied
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to clinical studies, and cell-based basic pharmacology and environmental medicine. Qualifications The applicant must hold a PhD degree, or have obtained one at the expected start date, in epidemiology
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Postdoc position within antibody engineering and therapy in Parkinson’s Disease We are seeking applicants for a 2-year postdoctoral position in Daniel Otzen’s research group at iNANO. This is a fix
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applicants will be offered Danish language training as part of the employment. The International Staff Office (ISO) at SDU provides a variety of services for new employees, guests and people who consider
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PDF file containing all materials to be given consideration. To apply, please open the link "Apply now", fill out the online application form, and attach all your materials in English in one PDF file
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collaboration with PI Associate Professor Mette Simonsen Abildgaard. Qualification Requirements • Applicants should hold a PhD in anthropology, STS, arctic studies, media studies or related fields
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and develop. We view equality and diversity as assets, and we welcome all applicants. International applicant? Aarhus University offers a broad variety of services for international researchers and
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environment with an emphasis on international collaboration. Your profile Applicants across the disciplines of physics, chemistry and biology are considered for this position. Outside of having a strong
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the online application form, and attach all your materials in English in one PDF file. The file must include: Application (cover letter) CV including contact information for at least two references Academic
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We are seeking highly motivated and talented applicants for a 1-year postdoctoral position (with the possibility of 1-2 year extension) in the area of efficient foundation model inference. Join us