Postdoctoral Fellowship in Biomedical Informatics

We are seeking a talented and motivated postdoctoral scholar to join our research team in developing state-of-the-art deep learning models, including large language models (LLMs), for predicting disease progression and outcomes using electronic medical records (EMRs). This is an exciting opportunity to contribute to the forefront of AI-driven healthcare innovation, leveraging big data to improve patient care and outcomes.

The successful candidate will focus on designing, training, and implementing novel deep learning models, particularly large language models, to analyze and interpret complex medical data from EMRs. The goal is to build predictive models that can forecast disease progression and patient outcomes, with applications across a variety of medical conditions. This position will involve close collaboration with data scientists, clinicians, and computational biologists in a multidisciplinary environment

The responsibilities: 

• Develop and apply cutting-edge deep learning models, including LLMs, to process and analyze large-scale EMR datasets.
• Design predictive models to assess disease trajectories, treatment outcomes, and patient risk factors.
• Integrate data from structured (e.g., lab results, medication records) and unstructured sources (e.g., clinical notes).
• Work closely with clinical experts to translate findings into actionable insights for improving patient care.
• Present research at conferences and contribute to peer-reviewed publications.