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Research Specialists

The Division of Epidemiology in the Department of Internal Medicine is seeking a Research Analyst 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.

Key Responsibilities

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

The department may choose to hire at any of the below job levels and associated pay rates based on their business need and budget.

Research Specialist, II

Set up and conduct experiments according to established research protocols while working under the direction of scientists. Perform a variety of tasks contributing to tests and studies to support the objectives of research projects. Prepare samples for analysis and perform laboratory tasks and procedures. Collect and analyze data, and test, validate, and document results. Summarize research findings to help inform decisions. Assist in the preparation of research documentation, such as grants, regulatory submissions, manuscripts, reports, summaries, publications, and presentations. Remain knowledgeable in the research methods, techniques, and developments in field of specialty. Requires moderate skill set and proficiency in discipline. Conducts work assignments of increasing complexity, under moderate supervision with some latitude for independent judgment.

Requires a bachelor's (or equivalency) + 4 years or a master's (or equivalency) + 2 years of directly related work experience.

This is a Developing-Level position in the General Professional track.

Job Code: P56432

Grade: P13

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 Specialist, II: Requires a bachelor's (or equivalency) + 4 years or a master's (or equivalency) + 2 years of directly related work experience.
Required

Educational background (completed a Bachelor's or Master's degree or currently enrolled in a Master's degree) in computing, data science, applied mathematics, medical/health 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 working independently in a Linux environment (shell scripting, package management, user and service configuration).

Ability to execute defined tasks independently while receiving structured requirements and 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.

Preferred

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.

Experience in writing and publishing scientific or technical work in peer-reviewed papers, whitepapers, technical articles, or blogs.

Submit 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.

The University is a participating employer with Utah Retirement Systems ("URS"). Eligible new hires with prior URS service, may elect to enroll in URS if they make the election before they become eligible for retirement (usually the first day of work). Contact Human Resources at (801) 581-7447 for information. Individuals who previously retired and are receiving monthly retirement benefits from URS are subject to URS' post-retirement rules and restrictions. Please contact Utah Retirement Systems at (801) 366-7770 or (800) 695-4877 or University Human Resource Management at (801) 581-7447 if you have questions regarding the post-retirement rules.
This position may require the successful completion of a criminal background check and/or drug screen.
The University of Utah values candidates who have experience working in settings with students and possess a strong commitment to improving access to higher education.
Veterans' preference is extended to qualified applicants, upon request and consistent with University policy and Utah state law. Upon request, reasonable accommodations in the application process will be provided to individuals with disabilities.
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