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demonstrated by documented experience of teaching with scientific foundation at university level. The criteria for evaluation are: an ability to plan, implement and evaluate teaching and an ability to supervise
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primarily in the medical, biomedical, pharmacy, and nursing programs. The department is located at the Biomedical Center (BMC) in Uppsala and has over 110 employees, including teachers, researchers, doctoral
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involve managing and mobilizing data from SITES thematic programs and research stations, but will also include maintaining SITES communication efforts and supporting other ongoing activities within
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background in biology, programming or mathematics is meritorious. Knowledge in medical image processing, image registration, and large-scale analyses of genetic (including Mendelian randomization), protein, or
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to fields such as critical theory, digital sociology, criminology, or science and technology studies (STS). As part of the application, the doctoral student will draft a brief plan for an independent project
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researchers at Lund University, Karlstad University and Södertörn University, and funded by The Wallenberg AI, Autonomous Systems and Software Program – Humanity and Society (WASP-HS). The research group
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efficiently interact in the interdisciplinary project. We seek candidates with a strong computer science, mathematics, statistics, or bioinformatics background and strong programming skills. Some previous
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advanced models for genomic selection to improve breeding programs in plant and animal breeding. You will analyze genetic data: Use bioinformatic and genomic methods to process and interpret large-scale
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into the WISE programme will be a part of the WISE Research School Who we are looking for The following requirements are mandatory: To qualify as a PhD student, you must have a Master's degree (masterexamen) of
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in integrative multi-omics as needed. The person we need The person we need have/is: • Strong programming skills, with proficiency in high-performance languages such as C, C++, or Python. • Familiarity