• Design and implement NLP pipelines in Python to extract, process, and analyze structured and unstructured clinical health data.
• Develop and validate text classification, named entity recognition, and/or information extraction models using libraries such as spaCy, Hugging Face Transformers, or other libraries.
• Clean, preprocess, and curate clinical datasets to ensure data quality and analytical readiness.
• Collaborate with the Principal Investigator to translate questions into computational analyses and interpret findings.
• Document code, analytical methods, and results in a clear and reproducible manner (e.g., Jupyter notebook).
• Present interim and final findings to the research team through written summaries and visual reports.
• Maintain confidentiality of protected health information (PHI).

Required

·       Excellent attention to detail, time management, and organizational skills.

·       Strong expressive and receptive communication skills.

·        Strong interest in clinical research, public health, or related fields.

·       Knowledge of Python

·       Knowledge of Natural Language Processing and machine learning classification models

Preferred

·       Knowledge of medical terminology.

·       Prior experience using Armis2 at the University of Michigan for Advanced Research Computing