Passionate about precision medicine and advancing the healthcare industry?
Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.
We are seeking a highly motivated and skilled Machine Learning Scientist to join our Digital Pathology Data Science team. In this role, you will play a key part in designing, developing, and deploying cutting-edge AI models and algorithms tailored to healthcare and precision medicine. Your work will help improve patient care, streamline clinical workflows, and advance medical research. This is an exciting opportunity to leverage the power of AI to transform healthcare and make a meaningful impact on people's lives.
Responsibilities:
- Develop and Implement AI/ML Models: Design, train, and validate machine learning models for analyzing digital pathology images (whole-slide images) to perform tasks like biomarkers and outcomes prediction.
- Algorithm Validation and Deployment: Validate ML/AI algorithms analytically and/or clinically, and deploy them into existing workflows or production environments.
- Data Analysis and Curation: Work with large-scale pathology datasets, ensuring data quality and integrity, collecting annotations, and preprocessing for model training and evaluation.
- Collaboration: Collaborate with a multidisciplinary team including pathologists, biologists, statisticians, data analysts, and engineers to integrate AI solutions and transform health care.
- Research and Innovation: Stay updated on the latest advancements in AI, machine learning, digital pathology, and multi-modal healthcare to contribute to ongoing projects and identify new opportunities.
- Biomarker Discovery: Assist in identifying biomarkers from histopathology and spatial omics data to support patient stratification and companion diagnostic efforts.
Required Experience:
- Ph.D. (or MS and 2+ years of working experience) in Computer Science, Artificial Intelligence, Data Science, Computational Biology, or a related field. A strong academic background with a focus on imaging for healthcare applications is preferred.
- Solid knowledge of machine learning concepts, including deep learning, optimization algorithms, regularization techniques, weakly supervised learning and self-supervised learning.
- Extensive experience in developing and implementing imaging AI models, such as ViT, CNNs, Unet, and related architectures including tasks such as classification, segmentation or detection.
- Outstanding analytical and problem-solving skills, with a particular focus on understanding the intricacies of multi-modal medical datasets.
- Proficiency in programming languages and packages commonly used in AI research, such as Python and PyTorch / Tensorflow.
- Strong collaboration and communication abilities.
- Track record in publications, patents, and/or launched products in this space.
Preferred Experience:
- Experience in pre-training and fine-tuning unimodal or multimodal foundation models.
- Experience working with histopathology images, DNA/RNA molecular sequencing data or clinical data (structured EHRs, clinical notes).
- Experience working in an industry setting.
