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Remote (United States)
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Intern
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Confirmed on the employer's own hiring board on Oct 19, 2026. First seen by Alion on Apr 16, 2026.

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Home Products WRDensity WRRisk About Research News Contact us Request demo Our Story Since our inception, we have been dedicated to creating innovative software solutions that tackle critical challenges in the breast cancer screening process.
Backed by Celesta

We are looking for a Research Scientist Intern to push the state of the art of our AI models. As a Research Scientist Intern 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.

Responsibilities

  • 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

Must Have Experience

  • Experience with deep learning and convolutional networks
  • Strong theoretical and empirical research background
  • Fluency with a deep learning framework and Python

Nice to Have Experience

  • Contributions to research communities and efforts, such as publications at conferences like CVPR, NeurIPS, ICCV, ECCV, ICML, and ICLR
  • Large scale machine learning experience working with terabytes of data
  • Implemented custom operations/modules in a deep learning framework
  • Imagination, ambition, and curiosity
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