206 data-"https:"-"https:"-"https:"-"https:"-"Institute-of-Astrophysics---FORTH" positions in Sweden
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members. More information about the department’s activities can be found here: www.uu.se/en/staff/department/immunology-genetics-and-pathology SciLifeLab (www.scilifelab.se ), established in 2010, is a hub
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on bioinformatics analysis of spatial gene expression data as well as other modalities (i.e. microbiome; metabolites, proteins) generated using the Spatial Transcriptomics (ST) method, Spatial metaTranscriptomics
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Additional Information Work Location(s) Number of offers available1Company/InstituteSciLifeLab / Uppsala UniversityCountrySwedenGeofield Contact Website https://scilifelab.se/ STATUS: EXPIRED X (formerly
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Information about the position Reference number REF 2026-0126 SciLifeLab (www.scilifelab.se ), established in 2010, is a hub for life science research in Sweden and a collaboration between Swedish
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molecular biology, evolution and biodiversity, precision medicine and diagnostics, epidemiology and biology of infection. For more information, please see https://www.scilifelab.se/data-driven/ddls-research
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Jönköping University and School of Engineering invites applications for a Lecturer in Computer Science with a focus on data science and machine learning. This position offers opportunities
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: cell and molecular biology, evolution and biodiversity, precision medicine and diagnostics, epidemiology and biology of infection. For more information, please see https://www.scilifelab.se/data-driven
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. For more information, please see https://www.scilifelab.se/data-driven/ddls-research-school/ Data driven epidemiology and biology of infection cover research that will transform our understanding
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11 Apr 2026 Job Information Organisation/Company Lunds universitet Department Lunds universitet Research Field Mathematics » Statistics Researcher Profile Recognised Researcher (R2) Application
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. For more information, please see https://www.scilifelab.se/data-driven/ddls-research-school/ Background and description of tasks Our group develops new single-cell multiomic methods to characterize microbial