Postdoctoral Positions in AI for Medicine and Pathology

UC Irvine; Irvine (CA); On-site; USD 66,737 - 80,034; Full time

Job summary

UC Irvine's OctoPath Lab seeks exceptional postdoctoral research fellows to develop deep learning and computational methods for pathology image analysis, multimodal data integration, and emerging medical modalities.

Ideal candidates hold a PhD, have a strong publication record, and are experienced in ML/DL, Python, and PyTorch; appointments are for two years with renewal based on performance.

Qualifications

• Strong understanding of ML and DL methods with hands-on model development experience.
• Proficiency in Python, C/C++, and DL libraries such as PyTorch.
• Experience in a team-oriented software development environment including Git, issue tracking, and code review.
• First-author publications in top journals/conferences.

Skills

ML/DL methods

Python

C/C++

PyTorch

Git

Education

PhD in Computer Science / Biomedical Engineering / Bioinformatics

Tools

Git

Job description

Position Overview

Salary range: $66,737–$80,034. The posted UC salary scales set the minimum pay determined by experience level. See: Postdoc Scholar Salary Scale.

Effective 10/1/26: The salary range is $71,491–$85,736. See: Postdoc Scholar Salary Scale.

Application Window

Open date: July 1, 2026.

Next review date: Saturday, Aug 1, 2026 at 11:59pm (Pacific Time). Apply by this date to ensure full consideration by the committee.

Final date: Wednesday, Jun 30, 2027 at 11:59pm (Pacific Time). Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.

Position Description

The OctoPath Lab led by Prof. Lipkova is seeking applications from exceptional postdoctoral research fellows interested in developing deep learning and computational methods for pathology image analysis, multimodal data integration, and other medical modalities (e.g., proteomics, spatial transcriptomics, genomics, radiology). Postdoctoral applicants should have a PhD, a solid publication record, and strong professional references. The ideal candidate should have a significant mathematical and computational background to learn and develop new AI methods. While demonstrated experience in computer vision and deep learning for pathology or other biomedical image analysis is desirable, applicants with a strong machine learning background and an interest in transitioning to biomedical data science are also encouraged to apply. Initial appointments are for two years and renewal is based on performance and available support.

Environment and Opportunities

The lab focuses on developing AI methods to improve patient diagnosis, prognosis, treatment response prediction, and treatment optimization. We are particularly interested in:
1) developing novel AI methods for analyzing pathology data,
2) multimodal data fusion strategies,
3) development of computational methods for rare diseases and new modalities (e.g., multiphoton microscopy), and
4) translating AI solutions into clinical practice through the development of AI-based embedded devices.
We are committed to applying these techniques to pressing clinical needs in medicine, including oncology, immunology, organ transplantation, and neurodegenerative diseases, while making our tools accessible to the research and medical communities. Our lab is part of the UCI School of Medicine which includes the Chao Family Comprehensive Cancer Center, one of the top National Cancer Institutes in USA, and we are affiliated with the UCI School of Biomedical Engineering. As part of UCI Health, we work with UCI’s main teaching hospital, the Douglas Hospital, as well as many of UCI’s recently acquired community hospitals. In addition, the lab benefits from proximity to healthcare startups, biotechnology firms, and a thriving biomedical community, allowing for networking and translational research opportunities. The lab has further strong collaboration with universities and medical centers across USA and Europe, offering exciting opportunities and a vibrant research environment.

Inquiries

Inquiries & questions should be directed to Prof. Jana Lipkova ([e-mail]).

Minimum Qualifications

• Appointment as a Postdoctoral Scholar requires a doctoral degree or working towards completion of a doctoral degree (e.g., PhD) or the foreign equivalent in Computer Science, Biomedical Engineering, Bioinformatics, or a related field.

Required Qualifications

• Strong understanding of machine learning (ML) and deep learning (DL) methods, with hands‑on experience in model development and application.
• Proficiency in programming languages such as Python, C, C++, and deep learning libraries like PyTorch or similar.
• Demonstrated ability to work in a team‑oriented software development environment, including experience with version control (e.g., Git), issue tracking, and code review.
• A track record of first‑author publications in top peer‑reviewed journals or conferences.

Preferred Qualifications

• Previous experience working with medical data and/or strong interest in AI methods in medical applications.
• Excellent scientific writing skills and oral communication abilities.
• Independent and self‑motivated with creative thinking and strong problem‑solving skills.
• Willingness to learn and adapt, including gaining medical knowledge related to specific diseases relevant to the lab's research focus.
• Committed to mentoring and fostering collaboration within a multidisciplinary team environment.

Application Requirements

• Curriculum Vitae (CV)
• Sample of coding skills, e.g., link to GitHub account
• Cover letter summarizing research interests, qualifications, and motivation to join the lab
• 3 References (contact information only)
• Up to 3 representative publications (links to publications are sufficient)

Lab

http://www.octopath.org

Apply Link

https://recruit.ap.uci.edu/JPF10254

Equal Opportunity Statement

The University of California, Irvine is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories covered by the UC anti-discrimination policy.

Employment Conditions

As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct.

Misconduct Definition

• “Misconduct” means any violation of the policies or laws governing conduct at the applicant’s previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment or discrimination, as defined by the employer.
• UC Sexual Violence and Sexual Harassment Policy
• UC Anti-Discrimination Policy for Employees, Students and Third Parties
• APM - 035: Aff…