Research Software Engineer, Radiotherapy, Health AI

About the job

At Google, research-focused Software Engineers are embedded throughout the company, allowing them to setup large-scale tests and deploy promising ideas quickly and broadly. Ideas may come from internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.

From creating experiments and prototyping implementations to designing new architectures, engineers work on real-world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. But you stay connected to your research roots as an active contributor to the wider research community by partnering with universities and publishing papers.

Google Health AI is an impact-focused research team that aims to catalyze the adoption of human-centered AI in healthcare and medicine. We see AI as transformational in these fields and a necessary component in realizing personalized medicine, expanding access for underserved populations, improving quality and consistency, deploying care at the edge, and closing the loop of a learning healthcare system. The Health AI team partners with other Google teams, external companies, non-profits, and governments to assess, develop, and deploy AI-powered breakthrough solutions that redefine the relationship between tech and health. The radiotherapy team within Health AI works to improve the quality of cancer treatment through the use of AI.

Google Health is a company-wide effort to help billions of people be healthier. We work toward this vision by meeting people in their everyday moments and empowering them to stay healthy and partnering with care teams to provide more accurate, accessible, and equitable care. Our teams are applying our expertise and technology to improve health outcomes globally – with high-quality information and tools to help people manage their health and wellbeing, solutions to transform care delivery, research to catalyze the use of artificial intelligence for the screening and diagnosis of disease, and data and insights to the public health community.

Responsibilities

• Train and analyze deep learning models to solve difficult problems in healthcare.
• Design and build tools to study application of models in a clinical setting.
• Work closely with a variety of internal and external stakeholders, including clinicians and research scientists.
• Pursue open-ended health research.
• Contribute to the publication of results in leading scientific journals.