RCI-ABBV-32947 Computational Biologist / Bioinformatics Scientist (Spatial Transcriptomics/Proteomics/Digital Pathology /Image Analysis/CosMx/Python/HALO)

• *Title: Scientist III, Computational Pathology

• *Remote role
• *Spatial Biology group
• *Candidate will do data analysis of generated spatial proteomics and transcriptomic data using PhenoCycler Fusion and CosMx
• *90% computational task and 10% pathology based work with scientist to interpret data
• *Bachelors degree with more than 10 yrs exp will be considered if they have spatial transcriptomic data analysis and CosMx experience
• *Computational 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)
• Python and R programming exp (must have)
• Work on existing pipelines and work on building pipeline
• Computational biology experience
• CosMx SMI (proteomics data analysis) experience (Must have)
• Exp in high-plex PhenoCycler Fusion (CODEX)
• Data analysis experience needed (must)
• 1 year of CosMx data analysis exp (Must have)
• spatial transcriptomic data analysis exp is needed (must have)
• Generate spatial proteomics and transcriptomic data using PhenoCycler Fusion and CosMx
• Data sets: Spatial transcriptomic and CosMx data sets on diff disease types
• Halo, Visiopharm, QuPath exp is nice to have
• *Must have:
• 1 year of CosMx data analysis exp (Must have)
• Python and R programming exp (must have)
• CosMx SMI (proteomics data analysis) experience (Must have)
• Spatial transcriptomic data analysis exp is needed (must have)
• *Purpose:
• The 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.
• The successful candidate will have advanced knowledge and experience analyzing spatial transcriptomics and proteomics data generated on the CosMx SMI and PhenoCycler Fusion platforms.
• *Responsibilities:
• Implementation of different scripts and pipelines for spatial transcriptomics data analysis and analysis of high-plex PhenoCycler Fusion (CODEX) images.
• Independently performing end-to-end high-plex image analysis (tissue classification, cell segmentation, detection of marker positivity, cell phenotyping, unsupervised clustering, neighborhood analysis, proximity analysis).
• Acting as a subject matter resource and training other team members in spatial analysis tasks.
• Collaborating with pathologists and digital pathology scientists to support spatial biology projects.
• Presenting the results and findings from spatial biology studies to stakeholders.
• *Qualifications:**

• MSc, PhD, or equivalent degree in biological sciences / computational biology / engineering / computer science / informatics

• Fluency in Python and R
• Experience in implementing and utilizing open-source scripts and pipelines for high-plex image analysis
• Experience in quantitative digital pathology analysis platforms such as Halo, Visiopharm, QuPath
• Close familiarity with tissue microscopic anatomy and histology (normal and diseased) is a plus
• Excellent verbal communication skills are required including the demonstrated ability to effectively and clearly summarize results for presentation and report generation
• Strong motivation, attention to detail, ability to think independently and fully integrate into a high achieving team environment
• Ability to multi-task and manage multiple projects

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