Posted on Friday, June 9, 2023
As a Research Scientist at Whiterabbit.ai, you will:
- Play a key role in architecting the algorithms and models that will power our products
- Train on a dedicated high-performance compute cluster specialized for deep learning research
- Work with doctors and healthcare professionals to identify serious problems and leverage their domain expertise to build robust solutions
- Remain an active contributor to the research community by partnering with universities and publishing high impact papers
Who we are:
Our mission at Whiterabbit.ai is to save lives and eliminate suffering through the early detection of cancer with artificial intelligence. We collaborate closely with one of the top medical schools in the country and have exclusive access to one of the world’s largest cancer datasets with millions of images. We invent algorithms that make doctors more productive, more accurate, and more capable. We build products and services with a relentless focus on transforming the patient’s healthcare experience.
- Develop highly scalable classifiers and detectors that solve real-world problems
- Learn and understand a large body of research in deep learning and machine learning
- Participate in cutting-edge research for medical applications of computer vision
- MS or PhD-level experience with deep learning and convolutional networks
- Contributions to research communities and efforts, such as publications at top tier conferences or high impact peer-reviewed journals
- Strong theoretical and empirical research background
- Extensive experience developing models for computer vision tasks (e.g. detection, classification, segmentation, domain adaptation) for real world problems.
- Ability to design, plan and carry out experiments to analyze and validate model performance.
- Fluency with Python and a deep learning framework, preferably PyTorch
Nice to Haves
- Large scale machine learning experience working with terabytes of data
- Experience working with and contributing to large multi-user code bases
- Experience conducting studies with physicians to evaluate AI performance and clinical implementation
- Experience with organizing, curating, and annotating datasets for computer vision problems
- Knowledge of medical imaging and DICOM data
- Imagination, ambition, and curiosity