Computational Pathology Scientist

At Gilead, we’re creating a healthier world for all people. For more than 35 years, we’ve tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer – working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world’s biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference.
 

Every member of Gilead’s team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we’re looking for the next wave of passionate and ambitious people ready to make a direct impact.
 

We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together.

Job Description
 

Gilead's mission is to discover, develop, and deliver therapies that will improve the lives of patients with life-threatening illnesses

worldwide.

The Computational Scientist, Pathobiology will be responsible for the following:

Job Description

The Research Pathobiology group at Gilead Sciences is seeking a talented and highly motivated imaging data scientist to advance discovery research and development projects at our Foster City, CA headquarters.

As part of the computational pathology team within Research Pathobiology, you will support imaging biomarker development efforts for clinical drug applications by:

• Analyzing pathology imaging data (e.g., H&E, IHC, CISH, mIF, CODEX, Spatial Transcriptomics) generated across Gilead’s drug development pipeline.
• Developing image analysis tools using commercial, internal, and open-source packages.
• Building automated image analysis pipelines for deployment on-premises and in cloud-based high-performance computing (HPC) environments.

The role requires extensive cross-functional collaboration with pathologists, biologists, biomarker scientists, data and imaging scientists, and IT personnel.

The primary focus is supporting image analysis initiatives, with an emphasis on developing and applying novel deep learning and machine learning approaches to advance our understanding of pathobiology in oncology, virology, fibrosis, and inflammation.

The candidate will also partner with clinical imaging and data management teams to deploy, maintain, and integrate computational solutions on HPC in the cloud.

Essential Duties and Job Functions: 

- Support the development of advanced analytics, computer vision, and computational tools to derive novel imaging-based biomarker endpoints.

- Collaborate with internal and external scientific partners to design, execute, and validate analytic strategies for tissue-based endpoints and imaging biomarkers supporting Gilead’s drug discovery and development pipelines.

- Evaluate and implement new computational approaches in digital pathology to extract histopathological endpoints and perform spatial analyses.

- Curate and prepare large imaging datasets for deep learning (DL) model training and development, including targeted models (tissue compartmentalization, cell phenotyping, etc.) and pathology foundation models.

- Contribute to imaging data management strategies and solutions within Gilead.

- Identify best practices and innovation opportunities relevant to image analysis projects.

- Effectively communicate findings and progress through reports, presentations, and publications for both expert and non-expert stakeholders.

Education/Basic Qualifications:

• PhD in a relevant quantitative field (e.g., Computer Science, Biomedical Engineering, Physics, Mathematics, Statistics); postdoctoral experience is a plus, OR
• MS degree in Computer Science/Biomedical Engineering with 4+ years of industry experience, OR
• BS degree in Computer Science/Biomedical Engineering with 6+ years of industry experience

Knowledge, Experience, and Skills: 

• Proficiency in deep learning and data science libraries such as PyTorch, Pandas, scikit-learn and NumPy; experience with image processing packages such as OpenSlide, OpenCV, MONAI, or Elastix is a plus.
• Demonstrated expertise in Python for scientific computing and imaging data analysis; experience with additional programming languages is a plus.
• Exten