46 python-"https:"-"CIPMM---Systemic-Neurophysiology" Postdoctoral positions in Sweden
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-on experience with R and/or Python, shell scripting, and Linux-based computational environments Experience with proteomics and/or metabolomics LC-MS data analysis is a strong advantage International research
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‑related aspects of nervous system function: https://ki.se/en/neuro/research/group-leaders-at-the-department-of-neuroscience SciLifeLab is a national research infrastructure providing unique technologies and
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Department of Clinical Microbiology The Dwibedi research group at the Department of Clinical Microbiology and the Laboratory for Molecular Infection Medicine Sweden (MIMS; https://www.mims.umu.se
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programming skills (e.g., Python) Previous experience with analyzing sequencing data Excellent communication abilities, and a collaborative mindset Meritorious for the position: Demonstrated work on developing
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manufacturing. It is meritorious to have previous experience in data analysis and processing with Python (or similar), preferably including documented experience with machine learning tools. It is meritorious
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charge detection. More information can be found at: www.ftf.lth.se , www.nano.lu.se https://portal.research.lu.se/en/persons/ville-maisi Subject description QPHOTON’s aim is to design, fabricate and
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, genetics, or related field • Expertise in genomic data analysis, particularly single-cell RNA-sequencing and/or alternative splicing • Strong background in bioinformatics and programming skills (e.g., Python
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on processing and analysis of metabolomics and exposomics data, covering both method development and applications. Background The systems medicine research group at Örebro University (https://www.oru.se/english
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academic progression More information: https://www.scilifelab.se/researchers/simon-koplev/ Qualifications Requirements A doctoral degree or an equivalent foreign degree. This eligibility requirement must be
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diseases. Programming knowledge in R or Python is a requirement. The applicant should also have experience in machine learning. Experience in analyzing multiple MRI modalities such as sMRI, DTI and fMRI is