Postdoctoral Fellow

Clinical Machine Learning We are investigating methods that learn from longitudinal, multi-modal data present in health data that (1) are predictive forecasters, and (2) preserve interrogable properties. The research will address the trustworthiness of EHR data for clinical decision making. Relevant experience includes expertise in representation learning, longitudinal data, ethical AI, annotation, curation, large-language models, and multi-modal learning, with applications in health domains. Relevant programmatic experience includes pytorch/huggingface/sklearn and R/tidyverse. Recent relevant publications:

1. Frattallone-Llado G, Kim J, Cheng C, Salazar D, Edakalavan S, Weiss JC. Using Multimodal Data to Improve Precision of Inpatient Event Timelines. In Pacific-Asia Conference on Knowledge Discovery and Data Mining 2024.
2. Cheng, C. and Weiss, JC. "Typed Markers and Context for Clinical Temporal Relation Extraction." Machine Learning for Healthcare. PMLR, 2023.
3. Noroozizadeh, S., Weiss, JC; and George Chen. “Temporal Supervised Contrastive Learning for Modeling Patient Risk Progression.” Machine Learning for Health, PMLR, 2023.

Compensation See the NIH Stipend Schedule (https://www.training.nih.gov/stipends/).

Fellows with a quantitative focus may receive an additional supplement of up to ten thousand dollars per annum. Start date: Spring– Summer 2025 Timing: postdoctoral fellowships are for 2 years with the possibility for extension. Candidates are subject to a background investigation. Applicants will be reviewed on a rolling basis.

• PhD and/or MD, or equivalent in related subject areas, including machine learning, computer science, medicine, bioinformatics, biomedical informatics and statistics/biostatistics;
• Clinical Machine Learning: Programming experience in python, pytorch and/or tensorflow; R, Julia, and/or C++
• Publishing experience with peer-reviewed journals or conferences in the above areas;
• Appointees may be U.S. citizens, permanent residents, or foreign nationals (visa requirements apply).

The NIH is dedicated to building a diverse community in its training and employment programs and encourages the application and nomination of qualified women, minorities, and individuals with disabilities. DHHS and NIH are Equal Opportunity Employers.