Postdoctoral Fellow

Company Description

Rutgers Robert Wood Johnson Medical School is one of the nation’s leading comprehensive medical schools, committed to excellence in education, research, healthcare delivery, and community health promotion. As part of New Jersey's premier academic medical center, it collaborates with Robert Wood Johnson University Hospital and 34 other hospital affiliates and ambulatory care sites across the region. With campuses in New Brunswick and Piscataway, the school educates more than 1,500 students across undergraduate, graduate, and postgraduate programs. It is home to 20 basic science and clinical departments and renowned institutes, including The Cardiovascular Institute, the Child Health Institute of New Jersey, and the Women’s Health Institute. Since 2013, it has been a part of Rutgers, The State University of New Jersey.

About the AiCCESS Lab

The AiCCESS Lab (Artificial Intelligence for Comprehensive Care, Equity & Sustainability in Surgery) at Rutgers Robert Wood Johnson Medical School is a rapidly growing, fully funded research laboratory at the forefront of clinical AI. Since our inception in late 2024, we have secured over $450K in active funding and built an international consortium of surgical AI experts with active collaborations at Johns Hopkins, Stanford, and the University of Florida.

We translate cutting-edge machine learning into real-world surgical tools — built for real patients, real operating rooms, and real outcomes.

Position Overview

We are seeking a highly motivated and technically skilled Postdoctoral Fellow to join our multidisciplinary team. This is a fully funded, full-time position focused on developing and deploying vision transformer models using multimodal surgical data to predict and prevent surgical site infections (SSIs) — one of the most consequential and costly complications in modern surgery.

This is not a siloed research role. You will work at the intersection of computer vision, clinical medicine, and implementation science, embedded in a team spanning surgery, computer science, and health systems research.

• 📅 Term: 1 year, renewable to 2 years
• 📍 Location: New Brunswick, NJ | Hybrid flexibility offered
• 🚨 Start Date: Immediate (ASAP)
• ⏰ Application Deadline: May 15, 2026

Key Responsibilities

• Design, train, and optimize vision transformer and multimodal deep learning models using surgical video, wound imaging, EHR data, and real-time sensor streams
• Develop and validate AI pipelines for intraoperative and postoperative SSI prediction
• Contribute to grant reporting, manuscript preparation, and conference presentations
• Mentor junior lab members and contribute to the lab's research culture

Required Qualifications

• PhD in Computer Science or Computational Biology
• Demonstrated expertise in computer vision, vision transformers, or multimodal deep learning
• Strong proficiency in Python and PyTorch and/or TensorFlow
• Track record of peer-reviewed publication or preprint output

Preferred Qualifications

• Experience with clinical or biomedical datasets (EHR, medical imaging, wearable/sensor data)
• Familiarity with cloud infrastructure (AWS) and clinical data platforms (REDCap, InfluxDB)
• Interest in translational AI and health equity
• Experience working in interdisciplinary or clinical research environments