PAIGE is leading the field of computational pathology by combining the world’s largest data set (over 25 million cancer pathology slides) and the most advanced team in AI and machine learning. PAIGE’s mission is to work alongside pathologists to build an AI that will improve the efficacy, objectivity, and scalability of their work.
We aim to build solutions for pathologists, clinicians and researchers to accelerate and improve the accuracy of cancer detection, classification, and staging. We work with hospitals to help gain insight from some of the largest digital tissue banks in the world to more efficiently and accurately read tissue samples. Data security and appropriate handling of data is a top priority for our team and our interdisciplinary team of computer scientists and clinical researchers work closely together with hospitals, such as Memorial Sloan Kettering Cancer Center, to identify and solve the tasks that make a real difference.
Candidates should expect to be embedded with AI researchers to develop QA frameworks and work with a complex clinical data pipeline, involving a range of technologies capabilities, static analysis/formal methods, and development to integrate with PAIGE’s HPC infrastructure.
- You hold a MS in computer science or related field
- You have strong experience with languages like C++, C#, and Python
- You have completed research in machine learning and computer vision and have deep understanding of statistics
- Experience with highly scalable machine learning frameworks that leverage GPU processing
- Experience with Linux, distributed systems and high performance computing
- You’ve worked in cross disciplinary teams and have great communication skills
Bonus points if you have:
- Contributed to open source projects
- Previous experience in the medical field, particularly with cancer research
To apply for this job please visit paigeai.bamboohr.com.