Sr. Research Scientist

* 2 + years of experience with a PhD in a relevant quantitative field (e.g., Computer Science, Biomedical Engineering, Physics, Mathematics, Statistics); postdoctoral experience is a plus, OR* 6 years + with an MS degree in Computer Science/Biomedical Engineering with 4+ years of industry experience, OR* 8+ years with a 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. #J-18808-Ljbffr