Director, Integrative Sciences
GSK
August 21, 2026
On-site
Collegeville, PA
Clinical Research and Development
Director of Emerging Diagnostic Technologies – Oncology Translational Medicine Integrative Sciences
Key Responsibilities:
- Lead innovation in emerging diagnostic technologies (ctDNA, computational pathology, advanced imaging, multi-modal biomarker platforms) to improve patient stratification, therapeutic targeting, and mechanism-of-action insights.
- Develop and apply oncology foundational models and AI/ML analytics to complex clinical/real-world/biomarker datasets (single-cell transcriptomics, spatial omics, proteomics, cfDNA).
- Serve as a subject-matter expert to enable biomarker discovery and diagnostic strategies optimizing patient selection, dose determination, and combination therapy (focus on ADCs).
- Oversee integration of oncology foundational models to inform translational medicine and clinical development strategies; ensure robust interpretation, implementation, and timely communication across teams.
- Collaborate cross-functionally (clinical development, CPMS, Diagnostics, Translational Research, AI/ML) to apply analytics approaches for insights into complex biology.
- Identify, evaluate, and implement emerging diagnostic platforms to advance innovation and pipeline growth.
- Communicate analysis outputs and models to technical and non-technical stakeholders.
- Champion biomarker/diagnostic strategy integration into clinical development plans.
- Drive computational pathology and AI-driven image analysis; support evaluation of academic/external partnerships; contribute to business development due diligence.
Basic Qualifications:
- PhD (or equivalent) in computational biology/bioinformatics/ML/computational pathology or related.
- 7+ years applied experience in pharma/biotech or academia (oncology research, diagnostic innovation, biomarker analysis).
- Ability to lead/influence cross-functional matrix teams.
- Experience with emerging diagnostic technologies in translational medicine/clinical development.
- Advanced statistical/analytical methods for high-dimensional heterogeneous data.
- Experience with GitHub, R Shiny/R Markdown, and cloud/HPC environments.
Preferred Qualifications:
- MD with oncology clinical development experience.
- Expertise in oncology foundational models and AI/ML for biomarker datasets.
- Coding proficiency (R/Python) and bioinformatics tools/databases.
- Experience analyzing high-dimensional datasets (single-cell/spatial transcriptomics, proteomics, cfDNA).
- Computational pathology and AI image analysis; clinical trial biomarker analysis; ADC biomarker/diagnostic strategies.
- Track record integrating preclinical/clinical biomarker data; familiarity with regulatory requirements/data standards.
Benefits/Compensation:
- Annual bonus and eligibility for share-based long-term incentive; US base salary range: $189,750–$316,250 (for specified US locations). Health care/insurance, retirement, paid holidays/vacation, and paid caregiver/parental and medical leave.
Application Instructions:
- (None provided in the excerpt.)
Key Responsibilities:
- Lead innovation in emerging diagnostic technologies (ctDNA, computational pathology, advanced imaging, multi-modal biomarker platforms) to improve patient stratification, therapeutic targeting, and mechanism-of-action insights.
- Develop and apply oncology foundational models and AI/ML analytics to complex clinical/real-world/biomarker datasets (single-cell transcriptomics, spatial omics, proteomics, cfDNA).
- Serve as a subject-matter expert to enable biomarker discovery and diagnostic strategies optimizing patient selection, dose determination, and combination therapy (focus on ADCs).
- Oversee integration of oncology foundational models to inform translational medicine and clinical development strategies; ensure robust interpretation, implementation, and timely communication across teams.
- Collaborate cross-functionally (clinical development, CPMS, Diagnostics, Translational Research, AI/ML) to apply analytics approaches for insights into complex biology.
- Identify, evaluate, and implement emerging diagnostic platforms to advance innovation and pipeline growth.
- Communicate analysis outputs and models to technical and non-technical stakeholders.
- Champion biomarker/diagnostic strategy integration into clinical development plans.
- Drive computational pathology and AI-driven image analysis; support evaluation of academic/external partnerships; contribute to business development due diligence.
Basic Qualifications:
- PhD (or equivalent) in computational biology/bioinformatics/ML/computational pathology or related.
- 7+ years applied experience in pharma/biotech or academia (oncology research, diagnostic innovation, biomarker analysis).
- Ability to lead/influence cross-functional matrix teams.
- Experience with emerging diagnostic technologies in translational medicine/clinical development.
- Advanced statistical/analytical methods for high-dimensional heterogeneous data.
- Experience with GitHub, R Shiny/R Markdown, and cloud/HPC environments.
Preferred Qualifications:
- MD with oncology clinical development experience.
- Expertise in oncology foundational models and AI/ML for biomarker datasets.
- Coding proficiency (R/Python) and bioinformatics tools/databases.
- Experience analyzing high-dimensional datasets (single-cell/spatial transcriptomics, proteomics, cfDNA).
- Computational pathology and AI image analysis; clinical trial biomarker analysis; ADC biomarker/diagnostic strategies.
- Track record integrating preclinical/clinical biomarker data; familiarity with regulatory requirements/data standards.
Benefits/Compensation:
- Annual bonus and eligibility for share-based long-term incentive; US base salary range: $189,750–$316,250 (for specified US locations). Health care/insurance, retirement, paid holidays/vacation, and paid caregiver/parental and medical leave.
Application Instructions:
- (None provided in the excerpt.)