Machine Learning Scientist, Radiology
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 an expert in image analysis, machine learning, and computer vision to join our imaging team as a Machine Learning Scientist.
What you’ll do:
As part of an interdisciplinary team, you will work on developing advanced image analysis techniques (segmentation, classification, object detection and prediction) to support precision medicine applications. The successful candidate will work collaboratively with a diverse team of Imaging Scientists, Radiologists, and Data Scientists; develop best-in-class algorithms that directly address important biological and clinical questions, and incorporate image-based data with clinical and molecular data to drive immuno-oncology research with the potential to expand to other disease areas.
- Advanced degree (Masters or Ph.D.) in computer science, biomedical engineering, biomedical imaging or a related field
- Experience building Computer Vision models for Radiographic images like CTs, MRIs, PET scans to derive disease phenotypes.
- Experience with applying modern registration, segmentation and classification techniques on Radiographic images. Good understanding of modern computer vision techniques like FCNs, domain adaptations, GRAD-CAM and GANs.
- Experience developing, training, and evaluating deep-learning models using public deep learning frameworks (e.g. PyTorch, TensorFlow, and Keras)
- Excellent communication skills and a collaborative mindset
- Record of meaningful scientific publications in high impact, technical or medical journals/conferences
- Experience with version control (GIT) and collaborative software development and testing
- Experience working with Docker containers and cloud-based compute environments
- Extensive knowledge in biology, especially medical or oncology-related.