You are viewing a preview of this job. Log in or register to view more details about this job.
Email

Professor Sarah Jabbour seeks a skilled and motivated individual to work as a full-time research professional (RP) for a period of at least one year. The start date is July 1, 2027 although earlier start dates are feasible. Applications are reviewed on a rolling basis. The first review is November 30, 2026, and application review will continue after this date until the position is filled 

 

Professor Jabbour is looking for an RP with a background in computer science, data science, or a related field, with an interest in one or more of the following topics: machine learning, computer vision, AI for health, biomedical informatics, or clinical AI. Specific research areas of interest to Professor Jabbour include: 

 

  1. Multimodal medical AI and representation learning from clinical data. This area focuses on developing machine learning models that integrate information from medical imaging, electronic health records, clinical notes, and other patient data. Projects may include multimodal modeling for clinical care (e.g., the diagnosis of hospitalized patients) and developing evaluation frameworks for medical AI. 
  2. AI-assisted clinical decision-making and clinician–AI collaboration.  This area focuses on understanding how clinicians interact with AI systems, when AI improves or harms decision-making, and how to design AI tools that better support clinical judgment. Projects may involve randomized human-subjects studies, evaluation of clinician behavior with AI assistance, and the design of workflows that account for both model performance and human behavior.

This role comes with significant research freedom and you can expect to be a first or co-first author on projects where you are a project lead. It is expected that you will have at least one paper during your time at Booth that will be submitted to a top venue. Potential venues include top AI/ML/CV conferences such as NeurIPS, ICML, ICLR, CVPR, ICCV, and ECCV; AI for health venues such as MLHC, CHIL, and ML4H; or clinical or biomedical journals.

For the types of research involved, please see Professor Jabbour’s prior work in multimodal AI, explainability in computer vision, and randomized trials of clinicians and AI (#1, #2). 

If interested, please fill out this online survey and this formal application. We pay a competitive salary and provide standard benefits such as health insurance.