Postdoctoral Research Fellow

Applications will be reviewed as they arrive, starting immediately, and will be accepted until the position is filled. For full consideration, we recommend that you apply early.

The Penn Computer Assisted Surgery and Outcomes (PCASO) Laboratory within Penn Surgery and the General Robotics, Automation, Sensing and Perception (GRASP) Laboratory at the University of Pennsylvania invites applications for a full-time postdoctoral fellow opening.

This postdoc will conduct research to develop the next generation of surgical data science algorithms including context awareness, scene understanding, workflow analysis, sim2real transfer, performance assessment, and lifelong learning. The postdoc will also collaborate with other researchers to apply these algorithms to robotic surgery, laparoscopy, flexible endoscopy, and trauma surgery. The ideal candidate would have a background in surgical data science, computer vision, lifelong learning, continual learning, deep learning, transfer learning, multi-task learning, reinforcement learning, semi-supervised methods, and/or Bayesian methods. Experience in machine perception would be helpful (but not necessary) as there are parallels to work in planning, navigation, and manipulation tasks in robotics.

In addition to conducting research on the above topics, the Fellows will have opportunities for mentoring students, assisting in the grant proposal process, and broad exposure to other researchers working on these projects.

These positions will be renewable for up to 2 years. A Ph.D. in computer science, electrical engineering, machine learning, robotics, or another closely related field is required. The position will report to Dr. Daniel Hashimoto with additional collaboration and mentorship from Drs. Kostas Daniilidis and Eric Eaton of Penn Engineering. The compensation package includes a competitive salary, health benefits, career mentoring, and conference travel support. The position offers opportunities to work with medical device industry collaborators and to be involved in leadership of national and international collaborative research projects.

Candidates should have a strong background in machine learning and/or robotics, supported by a solid publication record in top-tier machine learning, AI, robotics, and/or surgical conferences (e.g., MICCAI, AMIA, IPCAI, CARS, IROS, ICRA, NeurIPS, SAGES, American Surgical Association, etc.). Candidates should be familiar with Python and/or Julia programming in Linux-based environments, and other machine learning (e.g., PyTorch, Tensorflow, Keras) toolkits.

To apply, e-mail a single PDF file containing (1) a cover letter, (2) curriculum vitae, (3) research statement, (4) list of representative publications with URLs, and (5) list of references directly to Dr. Daniel Hashimoto ( ) with a subject line of "Postdoc Application: YOUR NAME". Please have 2-3 letters of recommendation sent directly to Dr. Hashimoto at with a subject line of "Postdoc Reference: YOUR NAME". Applications that do not follow the above instructions will not be considered, and no reply will be made.

The University of Pennsylvania is an Ivy League University located near the center of Philadelphia, the 5th largest city in the US. The University campus and the Philadelphia area support a rich diversity of scientific, educational, and cultural opportunities; major technology-driven industries such as pharmaceuticals, finance, and aerospace; as well as attractive urban and suburban residential neighborhoods. Princeton and New York City are within commuting distance.

The University of Pennsylvania is an Equal Opportunity/Affirmative Action Employer. Minority candidates and women are especially encouraged to apply. Hiring is contingent upon eligibility to work in the United States; if you are not a US-citizen and hired, Penn will work with the U.S. Government to obtain the necessary work permits. Questions can be directed to Dr. Daniel Hashimoto.