
Computational Pathology Scientist
- Foster City, CA
- $146,540-189,640 per year
- Permanent
- Full-time
- 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.
- 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
- 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.
- Extensive experience with DL models and architectures for image segmentation and classification such as ResNet, U-Net, and transformer-based models (e.g., ViT, Swin Transformer); familiarity with other ML algorithms (e.g., Logistic Regression, Random Forest, SVM)..
- Experience managing end-to-end ML/DL/AI projects, including data engineering, resource management, model training, selection, evaluation, and stakeholder communication.
- Up-to-date knowledge of advances in AI research and its application to medical imaging and digital pathology.
- Solid understanding of the mathematical and statistical foundations of machine learning and medical image analysis (e.g., optimization, image registration, segmentation, classification).
- Excellent written and verbal communication skills.
- Ability to multitask and prioritize while maintaining high standards of efficiency and quality.
- Self-motivated with a strong commitment to accuracy and excellence.
- Fluency in scientific computing environments (e.g., Unix/Linux shell), particularly in HPC and cloud-based clusters, is a plus.
- Publication record in deep learning, machine learning, or statistics, particularly in digital pathology, is a plus.
- Strong understanding of medical image data formats and challenges associated with large pathology images (e.g., WSI, CODEX, ST); experience analyzing whole-slide images is a plus.
- Experience with manipulating, analyzing, and visualizing large internal, public, and commercial imaging datasets is a plus.
- Familiarity with cell biology and microscopy is a plus.
- Create Inclusion - knowing the business value of diverse teams, modeling inclusion, and embedding the value of diversity in the
- Develop Talent - understand the skills, experience, aspirations and potential of their employees and coach them on current
- Empower Teams - connect the team to the organization by aligning goals, purpose, and organizational objectives, and holding
- Eligible employees may participate in benefit plans, subject to the terms and conditions of the applicable plans.