Applications for this role are now closed.
About the Program
The Google AI Residency Program (Healthcare) is a 12-month role designed to advance your career in machine learning research. Residents will work alongside distinguished scientists and engineers from the medical and healthcare teams, as well as collaborate with other Research teams. The goal of the residency is to help residents become successful AI researchers.
You have a background in healthcare and want to learn to conduct machine learning research in collaboration with our researchers. You may have research experience in another field (e.g., a medical specialty, epidemiology, healthcare delivery science, genomics, clinical informatics, bioinformatics, etc.) and want to apply machine learning to this area. Of course, already having machine learning research experience is great.
Participants must be able to commit to the full year of the program, on-site. Current doctoral students must graduate from their program before the residency begins. Physicians who are in residency or fellowship must either complete their training program before the AI Residency begins or be able to commit to a 12-month program (e.g., as part of a dedicated research year). We encourage candidates from all over the world to apply. If a candidate requires a work visa, Google will explore what options are available on a case-by-case basis.
The Google AI Residency Program (Healthcare) is based in the Bay Area and Residents will be expected to work on-site.
We do research differently here at Google. Our teams of Research Scientists are embedded throughout the engineering organization, allowing them to setup large-scale tests and deploy 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, Research Scientists 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. You may also stay connected to your research roots as an active contributor to the wider research community by partnering with universities and publishing papers.
To apply, please read all instructions below. To have a complete application, you will need a CV or Resume, cover letter, and transcript. More information below:
Your application should show evidence of a background in healthcare (e.g., experience as a physician, nurse, epidemiologist, healthcare delivery scientist, informatician, pharmacist, etc.), an interest in the field of machine learning in healthcare, evidence of research productivity (including peer-reviewed publications) and proficiency in programming. The latter could be demonstrated through peer-reviewed publications, masters- or doctoral-level coursework involving programming, notable performance in competitions, links to an open-source project that demonstrates programming, mathematical ability, or implementations of one or more novel learning algorithms, including an explanation for what makes it novel.
Prepare the following documents to complete your application:
- Current CV or resume (including links to Stack Overflow or similar online community, papers and/or blogs if applicable).
- Cover letter including a statement on why you think you'd be great for the Google AI Residency Program (Healthcare).
- Transcript if you are currently in school or have graduated in the last 3 years.
Click on the “Apply” button on this page to provide the above required materials in the appropriate sections (PDFs preferred):
- In the “Resume Section:” attach an updated CV or resume.
- In the “Cover letter/other notes Section:” Copy and paste your cover letter that includes a statement on why you think you'd be great for the Google AI Residency Program (Healthcare). **This section is mandatory for the program even though it is optional, as noted on the website, for other jobs at Google**.
- In the “Education Section:” attach a current or recent unofficial or official transcript in English.
- Under “Degree Status”, select “Now attending” to upload a transcript.
Questions? See our FAQ.
Learn and understand research in deep learning and/or machine learning algorithms.
Partner with research mentors to formulate research project(s) and/or novel application(s) of machine learning.
Conduct research and publish it in competitive venues.
Implement algorithms in TensorFlow.
A clinical degree (e.g., MD, RN, PharmD, etc.) or a healthcare-specific research-focused doctoral degree (e.g., PhD in Biostatistics, Epidemiology, or a related field).
Experience with quantitative research in healthcare, including peer-reviewed publications.
Experience with one or more programming languages.
Ability to participate for one full year on site.
Experience with machine learning approaches in healthcare data (e.g., publications, or links to open-source work or novel learning algorithms).
Expertise with research using complex healthcare data, for example, but not limited to: medical imaging, electronic health record or genomics data.
Contributions to machine learning research communities and/or efforts, including publishing papers in machine learning venues (e.g., JMLR, ICLR, NIPS, ICML, ACL and CVPR).
At Google, we don’t just accept difference - we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products and our community. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know.
To all recruitment agencies:
Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees or any other company location. Google is not responsible for any fees related to unsolicited resumes.