Job Summary

Daiichi Sankyo’s PhD Fellowship Program offers early-career scientists a unique opportunity to launch their careers at the forefront of drug development and innovation. This program is designed for recent PhD graduates and provides direct placement into a full-time role while offering structured development, mentorship, and visibility to leadership. 

This particular PhD Fellowship will be within the Precision Medicine Department with a core focus on Digital and Computational Pathology.

Program Features: 

• Direct Role Placement: Begin in a high-impact, business-critical role matched to your expertise
• Structured Development: Participate in tailored learning, professional skills workshops, and technical training
• Executive Exposure: Gain access to senior leaders and mentors across the organization 
• Peer Network: Join a cohort of PhD associates for shared learning and community
• Career Acceleration: Build a long-term path within Daiichi Sankyo through strategic guidance and performance development

Responsibilities

This role supports the development and evaluation of predictive biomarkers of patient treatment response enabled by computational pathology methods. The position involves both strategic and hands-on responsibilities related to the workflow of biomarker development from exploratory work to further development as companion diagnostics, including study design, model development and evaluation, and data analysis in a cross-functional setting.

• Develop and evaluate machine learning approaches leveraging vision foundation models for biomarker discovery in oncology. 
• Utilize large-scale oncology datasets, including H&E and IHC whole slide images and linked outcome data, to support model development and validation.
• Investigate strategies for extracting, aggregating, and interpreting feature embeddings from digital pathology data.
• Correlate model-derived features with clinical outcomes and asses their predictive utility.
• Relate identified biomarkers to drug mechanism of action to support translational research and therapeutic development.
• Collaborate with cross-functional teams including data scientists, pathologists, translational scientists, and clinicians.
• Contribute to study design, data analysis, and interpretation of results in an exploratory environment.
• Present findings internally and externally; contribute to scientific publications and conference presentations.

Qualifications

Education Qualifications

• PhD Data Science, Computer Science, Engineering, or a related quantitative field 

Experience Qualifications

• Demonstrated experience in machine learning/model development and image analysis (experience with digital pathology is a plus) preferred 
• Proficiency in Python and relevant ML/DL frameworks (e.g. Py Torch, Tensor Flow) preferred 
• Experience with vision foundation models, representation learning, or multimodal data integration preferred
• Familiarity with oncology data and/or biomarker development preferred
• Knowledge of clinical endpoints and translational research concepts preferred