Important Info
To apply, please submit the required application materials to (Leslie Johnson, MHSc) at (lesliejo@stanford.edu).
The highly motivated candidates should be passionate about the development and implementation of machine learning in clinical surgical settings and its implications on healthcare policy. This position offers a unique opportunity to first contribute to federally funded research on the advancement of real-time visualization of critical anatomical structures using hyperspectral optical imaging technology. The candidate will also work within the team to identify and contribute to other new research opportunities. The candidate must be able to work in a highly inter-disciplinary team of physicians, AI-scientists, and bioengineers. Specific responsibilities might include but are not limited to collection and processing of intraoperative imaging data, imaging instrument prototyping and problem-solving, patient-level clinical data collection and selecting and applying a variety of computational models towards novel clinical medical / surgical research domains.
The successful candidate will be based in the Department of Surgery at the Stanford University School of Medicine and will have opportunities to work with a diverse group of researchers. The fellowship has two primary goals: to advance the research program on artificial intelligence in surgery, and to develop the career and interests of the Fellow. This will include compiling and analyzing datasets, developing, training, and testing algorithms, presenting at national conferences and leading the drafting of manuscripts. In addition, the Fellow will have opportunities to partner and collaborate with faculty and programs across the University, other academic institutions and with our research partners in industry.
- Doctoral degree (PhD, or equivalent) or Physician with Masters level degree, preferably in Computer Science, Informatics/Biomedical Data Science, Engineering, Statistics, Computational Biology, or a related field
- Previous experience working with optical imaging, computer vision related to medical images, or machine learning in medical applications is a strong plus
- Experience applying other machine learning techniques to a variety of data types such as with time-series data or unstructured or multi-sensor data.
- Creative, highly motivated individuals with strong problem-solving skills, a record of scholarly productivity, and the ability to work independently, yet collaboratively, in a multidisciplinary environment with clinicians, computer scientists, and statisticians
- Excellent communication skills and fluency in both spoken and written English
- Strong command of large dataset management and analysis
- Experience in programming languages such as Stata, SAS, Python or R
- Proven record of peer-reviewed scientific publications
- Ability to learn and incorporate new skills and develop and modify them as needed
- Ability to work independently in the context of collaborations and generate complementary research ideas/demonstrate project leadership
- Contribute to and/or lab meetings and one-on-one discussions
- Cover letter that describes your research interests and background
- Current CV with publication list
- Contact information for three references
