Hourly Research Assistants

Hourly Research Assistants Job Summary The Division of Epidemiology in the Department of Internal Medicine is seeking a Research Assistant to support applied research at the intersection of healthcare, artificial intelligence, and data analysis. The primary focus of this role will be large language model (LLMs) and other machine learning model evaluation/deployment, clinical data pipeline development, and natural language processing (NLP)-based chart abstraction. The work will be performed using publicly available data, such as MIMIC-IV, and protected data from the University of Utah Health and the Veterans Health Administration within the UofU CHPC and VA VINCI secure computing environments. This position offers meaningful opportunities to engage in translational research that directly impacts patient care and health system operations. Job Duties Develop, maintain, and optimize data processing pipelines for clinical and research datasets using Python and SQL. Assist with the design, training, and evaluation of machine learning models applied to healthcare problems. Support research workflows within established Linux-based environments under technical supervision. Conduct exploratory data analysis and prepare visualizations and summary reports for research collaborators. Contribute to manuscript preparation, documentation, and reproducible research practices. Collaborate with clinical and research faculty, staff, and other trainees. Work within secure, access-controlled computing environments (e.g., VA VINCI, CHPC) following data governance and compliance requirements. Minimum Qualifications EQUIVALENCY STATEMENT: 1 year of higher education can be substituted for 1 year of directly related work experience (Example: bachelor's degree = 4 years of directly related work experience). Department may hire employee at one of the following job levels: Research Assistant I: Requires little to no related experience. Research Assistant II: Requires at least 1 year of related experience. Research Assistant III: Requires 3+ years of related experience. Currently enrolled master’s student in computing, informatics, data science, biomedical informatics, or a closely related discipline. Intermediate to advanced proficiency in Python and SQL. Experience applying NLP or machine learning methods to real‑world datasets (e.g., clinical text, scientific text, or similarly complex unstructured data). Intermediate to advanced experience with Linux system administration (shell scripting, package management, user and service configuration). Ability to execute defined tasks independently while receiving structured technical guidance. Availability to attend on‑site meetings or work in person for part of the scheduled time. This position requires eligibility for a VA appointment to access VA research systems (e.g., VINCI). Due to federal requirements, eligibility may be limited based on citizenship or visa status. Experience using or modifying machine learning models such as decision trees, Bayesian models, deep learning architectures, transformers, or LLMs. Familiarity with healthcare data standards (e.g., SNOMED CT, LOINC, RxNorm) or electronic health record systems. Experience with version control (Git/GitHub) and collaborative software development practices. Special Instructions Please submit your resume or CV, including relevant coursework, work experience, and technical skills. A link to your GitHub repository or portfolio of technical work and writing (peer‑reviewed papers or other technical/scientific articles, blogs, etc.) is strongly preferred. Applications will be reviewed on a rolling basis. #J-18808-Ljbffr The Chronicle Of Higher Education, Inc.