81 programming-"the"-"DAAD"-"IMPRS-ML"-"IDAEA-CSIC"-"U"-"UCL"-"https:" positions in Sweden
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include teaching in other areas of law, such as IT law. Teaching takes place both within the law programme and in other degree programmes. Duties include planning, conducting and evaluating teaching at both
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and in cell culture. Practical experience in programming with R. Practical experience in analytical methods including multiplex flow cytometry, as well as associated data analysis. Practical experience
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, and doctoral students. The department offers extensive doctoral education and coordinates two international Master's programmes as well as one Bachelor's programme. It has an established reputation
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and is responsible for education and research within medicine and healthcare. Our academic programs are closely linked with the healthcare system and are firmly anchored in the faculty’s strong research
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to the Master's Programme at the Umeå School of Architecture, including guidance and responding to questions related to the programme and the application process. Other tasks and duties may be assigned
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related field Proven methodological and research expertise Strong programming skills (Python, R, Bash or similar) for omics data processing, QC, statistical testing, and visualization to support biological
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and research within medicine and healthcare. Our academic programs are closely linked with the healthcare system and are firmly anchored in the faculty’s strong research tradition. Our research spans a
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) Experience in programming (Python or MATLAB) Strong analytical and problem-solving skills Excellent command of spoken and written English Ability to work independently and collaboratively in
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description The PhD student will: plan and conduct imaging studies on patients and healthy volunteers analyze image and perfusion data using LSCI, OCT, and HSI interpret physiological parameters and correlate
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programming, preferably using python or R Experience working with fMRI data Experience working with PET data Familiarity with git and GitHub Familiarity with best practices in reproducibility and open science