Summer 2026 - PhD Tissue based Multiomic Data Integration Internship
Bristol-Myers Squibb
Summer 2026 - PhD Tissue based Multiomic Data Integration Internship
Job Description
Integrate multi-omic datasets such as spatial transcriptomics/proteomics with metabolomics to identify ways to connect and interpret data from various tissue based platforms and technologies Integrate H&E and/or IHC datasets with high-plex spatial and metabolomic datasets to enable bidirectional mapping between low-plex and high-plex technologies Utilize AI-driven tools and R/Python packages to analyze and interpret data, work with CosMx GitHub repositories and handling Seurat objects, spatial location files, CSVs and related formats. Perform clustering, differential expression, pathway enrichment, and spatial proximity analysis and familiarity with image analysis. Collaborate across CROs externally and internally with translational and bioinformatics teams. Present findings and contribute to internal reports. Work-life programs include paid national holidays and optional holidays, Global Shutdown Days between Christmas and New Year's holiday, up to 120 hours of paid vacation, up to two (2) paid days to volunteer, sick time off, and summer hours flexibility. Enrolled in a PhD program in Bioinformatics, Computational Biology, Biomedical Engineering, Pathology, Oncology. Experience with spatial platforms (CosMx preferred) and image analysis. Familarity with FFPE tissue. Proficiency in R or Python; familiarity with Seurat and pathway analysis tools (e.g., GSEA, IPA, Reactome). Courses in oncology and immunology. Strong attention to details and organizational skills. Ability to clearly communicate and operate in a local, and highly matrixed environment. All candidates must be authorized to work in the US both at the time of hire and for the duration of their employment. Please note that immigration or visa sponsorship is not available for this position.
Key Responsibilities
- Integrate multi-omic datasets such as spatial transcriptomics/proteomics with metabolomics
- Connect and interpret data from various tissue-based platforms and technologies
- Integrate H&E and/or IHC datasets with high-plex spatial and metabolomic datasets
- Enable bidirectional mapping between low-plex and high-plex technologies
- Utilize AI-driven tools and R/Python packages to analyze and interpret data
- Work with CosMx GitHub repositories and handle Seurat objects, spatial location files, CSVs, and related formats
- Perform clustering, differential expression, pathway enrichment, and spatial proximity analysis
- Collaborate across CROs externally and internally with translational and bioinformatics teams
- Present findings and contribute to internal reports
Required Qualifications
- Enrolled in a PhD program in Bioinformatics, Computational Biology, Biomedical Engineering, Pathology, or Oncology
Preferred Qualifications
- Experience with spatial platforms, specifically CosMx
- Familiarity with FFPE tissue
- Courses in oncology and immunology
Skills Required
- Proficiency in R or Python
- Familiarity with Seurat and pathway analysis tools (e.g., GSEA, IPA, Reactome)
- Familiarity with image analysis
- Strong attention to details and organizational skills
- Ability to clearly communicate and operate in a local, and highly matrixed environment
Benefits & Perks
- Paid national holidays and optional holidays
- Global Shutdown Days between Christmas and New Year's holiday
- Up to 120 hours of paid vacation
- Up to two (2) paid days to volunteer
- Sick time off
- Summer hours flexibility
Additional Requirements
- Must be authorized to work in the US both at the time of hire and for the duration of employment
- Immigration or visa sponsorship is not available for this position
Locations
- Seattle 400 Dexter WA, United States
Salary
Estimated Salary Rangemedium confidence
50,000 - 70,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Proficiency in R or Pythonintermediate
- Familiarity with Seurat and pathway analysis tools (e.g., GSEA, IPA, Reactome)intermediate
- Familiarity with image analysisintermediate
- Strong attention to details and organizational skillsintermediate
- Ability to clearly communicate and operate in a local, and highly matrixed environmentintermediate
Required Qualifications
- Enrolled in a PhD program in Bioinformatics, Computational Biology, Biomedical Engineering, Pathology, or Oncology (experience)
Preferred Qualifications
- Experience with spatial platforms, specifically CosMx (experience)
- Familiarity with FFPE tissue (experience)
- Courses in oncology and immunology (experience)
Responsibilities
- Integrate multi-omic datasets such as spatial transcriptomics/proteomics with metabolomics
- Connect and interpret data from various tissue-based platforms and technologies
- Integrate H&E and/or IHC datasets with high-plex spatial and metabolomic datasets
- Enable bidirectional mapping between low-plex and high-plex technologies
- Utilize AI-driven tools and R/Python packages to analyze and interpret data
- Work with CosMx GitHub repositories and handle Seurat objects, spatial location files, CSVs, and related formats
- Perform clustering, differential expression, pathway enrichment, and spatial proximity analysis
- Collaborate across CROs externally and internally with translational and bioinformatics teams
- Present findings and contribute to internal reports
Benefits
- general: Paid national holidays and optional holidays
- general: Global Shutdown Days between Christmas and New Year's holiday
- general: Up to 120 hours of paid vacation
- general: Up to two (2) paid days to volunteer
- general: Sick time off
- general: Summer hours flexibility
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Answer 10 quick questions to check your fit for Summer 2026 - PhD Tissue based Multiomic Data Integration Internship @ Bristol-Myers Squibb.
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Summer 2026 - PhD Tissue based Multiomic Data Integration Internship
Bristol-Myers Squibb
Summer 2026 - PhD Tissue based Multiomic Data Integration Internship
Job Description
Integrate multi-omic datasets such as spatial transcriptomics/proteomics with metabolomics to identify ways to connect and interpret data from various tissue based platforms and technologies Integrate H&E and/or IHC datasets with high-plex spatial and metabolomic datasets to enable bidirectional mapping between low-plex and high-plex technologies Utilize AI-driven tools and R/Python packages to analyze and interpret data, work with CosMx GitHub repositories and handling Seurat objects, spatial location files, CSVs and related formats. Perform clustering, differential expression, pathway enrichment, and spatial proximity analysis and familiarity with image analysis. Collaborate across CROs externally and internally with translational and bioinformatics teams. Present findings and contribute to internal reports. Work-life programs include paid national holidays and optional holidays, Global Shutdown Days between Christmas and New Year's holiday, up to 120 hours of paid vacation, up to two (2) paid days to volunteer, sick time off, and summer hours flexibility. Enrolled in a PhD program in Bioinformatics, Computational Biology, Biomedical Engineering, Pathology, Oncology. Experience with spatial platforms (CosMx preferred) and image analysis. Familarity with FFPE tissue. Proficiency in R or Python; familiarity with Seurat and pathway analysis tools (e.g., GSEA, IPA, Reactome). Courses in oncology and immunology. Strong attention to details and organizational skills. Ability to clearly communicate and operate in a local, and highly matrixed environment. All candidates must be authorized to work in the US both at the time of hire and for the duration of their employment. Please note that immigration or visa sponsorship is not available for this position.
Key Responsibilities
- Integrate multi-omic datasets such as spatial transcriptomics/proteomics with metabolomics
- Connect and interpret data from various tissue-based platforms and technologies
- Integrate H&E and/or IHC datasets with high-plex spatial and metabolomic datasets
- Enable bidirectional mapping between low-plex and high-plex technologies
- Utilize AI-driven tools and R/Python packages to analyze and interpret data
- Work with CosMx GitHub repositories and handle Seurat objects, spatial location files, CSVs, and related formats
- Perform clustering, differential expression, pathway enrichment, and spatial proximity analysis
- Collaborate across CROs externally and internally with translational and bioinformatics teams
- Present findings and contribute to internal reports
Required Qualifications
- Enrolled in a PhD program in Bioinformatics, Computational Biology, Biomedical Engineering, Pathology, or Oncology
Preferred Qualifications
- Experience with spatial platforms, specifically CosMx
- Familiarity with FFPE tissue
- Courses in oncology and immunology
Skills Required
- Proficiency in R or Python
- Familiarity with Seurat and pathway analysis tools (e.g., GSEA, IPA, Reactome)
- Familiarity with image analysis
- Strong attention to details and organizational skills
- Ability to clearly communicate and operate in a local, and highly matrixed environment
Benefits & Perks
- Paid national holidays and optional holidays
- Global Shutdown Days between Christmas and New Year's holiday
- Up to 120 hours of paid vacation
- Up to two (2) paid days to volunteer
- Sick time off
- Summer hours flexibility
Additional Requirements
- Must be authorized to work in the US both at the time of hire and for the duration of employment
- Immigration or visa sponsorship is not available for this position
Locations
- Seattle 400 Dexter WA, United States
Salary
Estimated Salary Rangemedium confidence
50,000 - 70,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Proficiency in R or Pythonintermediate
- Familiarity with Seurat and pathway analysis tools (e.g., GSEA, IPA, Reactome)intermediate
- Familiarity with image analysisintermediate
- Strong attention to details and organizational skillsintermediate
- Ability to clearly communicate and operate in a local, and highly matrixed environmentintermediate
Required Qualifications
- Enrolled in a PhD program in Bioinformatics, Computational Biology, Biomedical Engineering, Pathology, or Oncology (experience)
Preferred Qualifications
- Experience with spatial platforms, specifically CosMx (experience)
- Familiarity with FFPE tissue (experience)
- Courses in oncology and immunology (experience)
Responsibilities
- Integrate multi-omic datasets such as spatial transcriptomics/proteomics with metabolomics
- Connect and interpret data from various tissue-based platforms and technologies
- Integrate H&E and/or IHC datasets with high-plex spatial and metabolomic datasets
- Enable bidirectional mapping between low-plex and high-plex technologies
- Utilize AI-driven tools and R/Python packages to analyze and interpret data
- Work with CosMx GitHub repositories and handle Seurat objects, spatial location files, CSVs, and related formats
- Perform clustering, differential expression, pathway enrichment, and spatial proximity analysis
- Collaborate across CROs externally and internally with translational and bioinformatics teams
- Present findings and contribute to internal reports
Benefits
- general: Paid national holidays and optional holidays
- general: Global Shutdown Days between Christmas and New Year's holiday
- general: Up to 120 hours of paid vacation
- general: Up to two (2) paid days to volunteer
- general: Sick time off
- general: Summer hours flexibility
Tags & Categories
Answer 10 quick questions to check your fit for Summer 2026 - PhD Tissue based Multiomic Data Integration Internship @ Bristol-Myers Squibb.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs