Scientist, Translational Pathology, Oncology
About The Position
Are you ready to turn digital pathology into decisions that shape cancer trials and treatments? Join a team advancing oncology by fusing laboratory automation, image analysis, and data science to surface the signals that matter for patients. You will sit at the intersection of biology, engineering, and AI, transforming tissue images and lab data into robust, decision-ready insights. In this role, you will accelerate how we understand disease biology and therapeutic response. Working with Translational Pathology and partners across Oncology R&D, you will industrialize automated lab workflows and deploy modern machine learning to quantify biomarkers and the tumor microenvironment. How will you use your craft to influence indication selection, dose and schedule decisions, and rational combination strategies that reach the clinic faster?
Requirements
- Bachelor's or Master's degree in a relevant field (e.g., biology, computer science, engineering or other relevant subject) and 3 years relevant experience.
- Expertise in implementation of laboratory automation
- Python proficiency is required with experience in automation and pipeline development.
- Working knowledge of deep learning architectures, Foundation models optimization and fine tuning.
- Data visualization and data science experience (R and/or python experience strongly preferred)
- Git workflow and versioning control for coding in a collaborative, corporate environment
Nice To Haves
- Creation and deployment of flask, streamlit, and other web-based apps
- Use of agentic and generative AI to create automated systems for non-coders
- Experience in image analysis (e.g. Qupath, HALO/HALO link and Visiopharm)
- Experience of immunohistochemistry and/or handling immunohistochemistry data
- Knowledge of GxP systems and requirements
- Career exposure to the pharmaceutical industry and the drug development process.
- Skilled in effective communication of complex data to a non-expert.
- Enthusiasm and persistence in the application of analytic methods to complex biological problems.
- Capability of successfully managing multiple simultaneous projects within an agile environment.
- Working effectively within cross-disciplinary science teams, including functional leaders.
Responsibilities
- Design, implement, and scale automated workflows that increase throughput, reduce error, and elevate data quality across translational pathology laboratories.
- Build, test, and maintain reliable Python-based pipelines with robust version control to ingest, process, and serve high-quality datasets for downstream analysis and decision-making.
- Apply deep learning and foundation models to immunohistochemistry whole-slide images to quantify target expression and tumor microenvironment changes; validate and operationalize models for routine use.
- Integrate preclinical, clinical, and commercial tissue data; create clear visual narratives in R/Python that enable confident, timely decisions.
- Connect image-derived and molecular signals to disease biology, guiding indication selection and defining targeted patient populations.
- Quantify drug-target engagement and pharmacodynamic effects to support selection of therapeutically relevant doses and schedules.
- Partner with pathologists, biologists, clinicians, and engineers; communicate complex analyses to non-experts; align stakeholders on evidence-based decisions.
- Embed rigorous documentation, GxP awareness, and reproducible practices; manage multiple projects in an agile environment while continuously improving tools and methods.
Benefits
- qualified retirement programs
- paid time off (i.e., vacation, holiday, and leaves)
- health, dental, and vision coverage
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
Associate degree
