{"schemaVersion":"jobsearcher.job.v1","id":"464c6b1c61bb8678265cd633","url":"https://jobsearcher.com/jobs/464c6b1c61bb8678265cd633","canonicalUrl":"https://jobsearcher.com/jobs/464c6b1c61bb8678265cd633","title":"Computational Pathology Scientist (CosMx SMI/Python/R Programming)","description":"Title: Scientist III, Computational Pathology\nRemote role\nSpatial Biology group\nCandidate will do data analysis of generated spatial proteomics and transcriptomic data using PhenoCycler Fusion and CosMx\n90% computational task and 10% pathology based work with scientist to interpret data\nBachelors degree with more than 10 yrs exp will be considered if they have spatial transcriptomic data analysis and CosMx experience\nComputational biologist who are familiar with looking at pathology images would also work and able to contribute the interpretations (Must have understanding of pathology and biology of disease)\nPython and R programming exp (must have)\nWork on existing pipelines and work on building pipeline\nComputational biology experience\nCosMx SMI (proteomics data analysis) experience (Must have)\nExp in high-plex PhenoCycler Fusion (CODEX)\nData analysis experience needed (must)\n1 year of CosMx data analysis exp (Must have)\nspatial transcriptomic data analysis exp is needed (must have)\nGenerate spatial proteomics and transcriptomic data using PhenoCycler Fusion and CosMx\nData sets: Spatial transcriptomic and CosMx data sets on diff disease types\nHalo, Visiopharm, QuPath exp is nice to have\nMust have:\n1 year of CosMx data analysis exp (Must have)\nPython and R programming exp (must have)\nCosMx SMI (proteomics data analysis) experience (Must have)\nSpatial transcriptomic data analysis exp is needed (must have)\nPurpose:\nThe Precision Medicine Pathology team drives the scientific strategy for translational tissue-based biomarker development & discovery target validation/MOA projects, leads pathology collaborative programs, conducts histopathological evaluation & analysis of IHC & spatial biology technologies, and provides technical/scientific leadership to histotechnicians & pathology scientists.\nThe successful candidate will have advanced knowledge and experience analyzing spatial transcriptomics and proteomics data generated on the CosMx SMI and PhenoCycler Fusion platforms.\nResponsibilities:\nImplementation of different scripts and pipelines for spatial transcriptomics data analysis and analysis of high-plex PhenoCycler Fusion (CODEX) images.\nIndependently performing end-to-end high-plex image analysis (tissue classification, cell segmentation, detection of marker positivity, cell phenotyping, unsupervised clustering, neighborhood analysis, proximity analysis).\nActing as a subject matter resource and training other team members in spatial analysis tasks.\nCollaborating with pathologists and digital pathology scientists to support spatial biology projects.\nPresenting the results and findings from spatial biology studies to stakeholders.\nQualifications:\nMSc, PhD, or equivalent degree in biological sciences / computational biology / engineering / computer science / informatics\nFluency in Python and R\nExperience in implementing and utilizing open-source scripts and pipelines for high-plex image analysis\nExperience in quantitative digital pathology analysis platforms such as Halo, Visiopharm, QuPath\nClose familiarity with tissue microscopic anatomy and histology (normal and diseased) is a plus\nExcellent verbal communication skills are required including the demonstrated ability to effectively and clearly summarize results for presentation and report generation\nStrong motivation, attention to detail, ability to think independently and fully integrate into a high achieving team environment\nAbility to multi-task and manage multiple projects\nJob Type: Contract\nPay: $76.00 - $78.00 per hour\nExpected hours: 40 per week\nBenefits:\nHealth insurance\nEducation:\nBachelor's (Preferred)\nExperience:\nhigh-plex image analysis: 3 years (Preferred)\nPython: 3 years (Preferred)\nR programming: 3 years (Preferred)\nCosMx SMI: 1 year (Preferred)\nanalyzing spatial transcriptomics and proteomics data: 3 years (Preferred)\nWork Location: Remote","company":"Systemsally","rawCompany":"systemsally","city":"Remote","state":"OR","isRemote":false,"isActive":false,"createdAt":"2026-08-06T12:58:29.949Z","occupations":[{"code":"19-1029.01","title":"Bioinformatics Scientists","slug":"bioinformatics-scientists"},{"code":"29-1222.00","title":"Physicians, Pathologists","slug":"physicians-pathologists"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"}],"industries":[{"code":"541714","title":"Research and Development in Biotechnology (except Nanobiotechnology)","slug":"research-and-development-in-biotechnology-except-nanobiotechnology"},{"code":"621511","title":"Medical Laboratories","slug":"medical-laboratories"},{"code":"541715","title":"Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)","slug":"research-and-development-in-the-physical-engineering-and-life-sciences-except-nanotechnology-and-biotechnology"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Computational Pathology Scientist (CosMx SMI/Python/R Programming)","description":"Title: Scientist III, Computational Pathology\nRemote role\nSpatial Biology group\nCandidate will do data analysis of generated spatial proteomics and transcriptomic data using PhenoCycler Fusion and CosMx\n90% computational task and 10% pathology based work with scientist to interpret data\nBachelors degree with more than 10 yrs exp will be considered if they have spatial transcriptomic data analysis and CosMx experience\nComputational biologist who are familiar with looking at pathology images would also work and able to contribute the interpretations (Must have understanding of pathology and biology of disease)\nPython and R programming exp (must have)\nWork on existing pipelines and work on building pipeline\nComputational biology experience\nCosMx SMI (proteomics data analysis) experience (Must have)\nExp in high-plex PhenoCycler Fusion (CODEX)\nData analysis experience needed (must)\n1 year of CosMx data analysis exp (Must have)\nspatial transcriptomic data analysis exp is needed (must have)\nGenerate spatial proteomics and transcriptomic data using PhenoCycler Fusion and CosMx\nData sets: Spatial transcriptomic and CosMx data sets on diff disease types\nHalo, Visiopharm, QuPath exp is nice to have\nMust have:\n1 year of CosMx data analysis exp (Must have)\nPython and R programming exp (must have)\nCosMx SMI (proteomics data analysis) experience (Must have)\nSpatial transcriptomic data analysis exp is needed (must have)\nPurpose:\nThe Precision Medicine Pathology team drives the scientific strategy for translational tissue-based biomarker development & discovery target validation/MOA projects, leads pathology collaborative programs, conducts histopathological evaluation & analysis of IHC & spatial biology technologies, and provides technical/scientific leadership to histotechnicians & pathology scientists.\nThe successful candidate will have advanced knowledge and experience analyzing spatial transcriptomics and proteomics data generated on the CosMx SMI and PhenoCycler Fusion platforms.\nResponsibilities:\nImplementation of different scripts and pipelines for spatial transcriptomics data analysis and analysis of high-plex PhenoCycler Fusion (CODEX) images.\nIndependently performing end-to-end high-plex image analysis (tissue classification, cell segmentation, detection of marker positivity, cell phenotyping, unsupervised clustering, neighborhood analysis, proximity analysis).\nActing as a subject matter resource and training other team members in spatial analysis tasks.\nCollaborating with pathologists and digital pathology scientists to support spatial biology projects.\nPresenting the results and findings from spatial biology studies to stakeholders.\nQualifications:\nMSc, PhD, or equivalent degree in biological sciences / computational biology / engineering / computer science / informatics\nFluency in Python and R\nExperience in implementing and utilizing open-source scripts and pipelines for high-plex image analysis\nExperience in quantitative digital pathology analysis platforms such as Halo, Visiopharm, QuPath\nClose familiarity with tissue microscopic anatomy and histology (normal and diseased) is a plus\nExcellent verbal communication skills are required including the demonstrated ability to effectively and clearly summarize results for presentation and report generation\nStrong motivation, attention to detail, ability to think independently and fully integrate into a high achieving team environment\nAbility to multi-task and manage multiple projects\nJob Type: Contract\nPay: $76.00 - $78.00 per hour\nExpected hours: 40 per week\nBenefits:\nHealth insurance\nEducation:\nBachelor's (Preferred)\nExperience:\nhigh-plex image analysis: 3 years (Preferred)\nPython: 3 years (Preferred)\nR programming: 3 years (Preferred)\nCosMx SMI: 1 year (Preferred)\nanalyzing spatial transcriptomics and proteomics data: 3 years (Preferred)\nWork Location: Remote","datePosted":"2026-08-06T12:58:29.949Z","dateModified":"2026-08-06T12:58:29.949Z","hiringOrganization":{"@type":"Organization","name":"Systemsally","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote","addressRegion":"OR","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"464c6b1c61bb8678265cd633"},"url":"https://jobsearcher.com/jobs/464c6b1c61bb8678265cd633"}}