Research Scientist II - Health and Clinical Outcomes Research

DEPT MARKETING STATEMENT:UTMB’s new Center for Health and Clinical Outcomes Research (H-COR) seeks Research Scientists to advance decision-grade evidence from real-world data to study and understand human health. H-COR leverages Epic EHR (Clarity/Caboodle and Cosmos), TriNetX, Medicare and other administrative data. H-COR has an interest in pairing outcomes research with secure, principled integration of high-dimensional modalities (e.g., transcriptomics, proteomics, pathogen genomics). Also of interest is the utilization of novel data sources including those derived from social media, mobile phones, wearables, and other digital sources. Researchers at H-COR collaborate across all five UTMB schoolsJOB DESCRIPTION: Conducts innovative scientific investigation by developing theories and devising scientific methods and procedures to apply scientific principles, theories and research in projects related to the mission of UTMB. Committed to the discovery of new innovative biomedical and health services knowledge leading to increasingly effective and accessible health care. Assures competence as a fully trained scientist in a specific discipline or area of expertise.ESSENTIAL JOB FUNCTIONS:Leading and contributing to high-impact health and clinical outcomes researchPlanning and performing advanced data analyses using UTMB's exceptional data infrastructure, with particular emphasis on electronic health record (EHR) data including EPIC, EPIC Cosmos, TriNetX, and Medicare administrative datasetsBuilding transparent cohort definitions and phenotypes using ICD-10/PCS, CPT/HCPCS, LOINC, and RxNormImplementing modern causal-inference strategies (e.g., target-trial emulation, robust confounding control, time-to-event and longitudinal models, principled handling of missingness, falsification and sensitivity analyses)Collaborating across UTMB’s schools on defined research programsContributing to abstracts, manuscripts, and grant applications as PI/Co-I or key personnelIntegrating clinical timelines with multi-omics and other high-dimensional data while preserving clinical interpretability and privacyPresenting research at professional meetings and conferencesParticipating in H-COR's monthly works-in-progress seminarsMINIMUM QUALIFICATIONS:Ph. D, M.D, D.O., or D.V.M in related field and one year of related experience.PREFERRED QUALIFICATIONS:PhD or equivalent doctoral degree in a relevant discipline (health services research, epidemiology, biostatistics, data science, computer science, or a closely related field)A track record in health and clinical outcomes methodsDemonstrated expertise analyzing clinical and population-health data with specific experience in EHR analyticsProficiency with large healthcare databases (Epic, Epic Cosmos, TriNetX, Medicare)Fluency in at least two of R, Python, SAS, and SQLExcellent scientific writing and communicationEvidence of peer-reviewed publications commensurate with career stageExperience with OMOP and HL7 FHIR data modelsHands-on practice with target-trial emulation and advanced propensity and longitudinal methodsClinically oriented NLP and time-aware feature extractionFamiliarity with multi-omics data structures and cautious EHR-omics linkageExperience in HPC or cloud settings (e.g., TACC, Azure, AWS) and workflow engines that promote end-to-end reproducibilityMentorship of analysts or traineesA record of effective, cross-disciplinary collaboration in an academic health-sciences environmentSALARY:Commensurate with experience.EQUAL EMPLOYMENT OPPORTUNITY:UTMB Health strives to provide equal opportunity employment without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, genetic information, disability, veteran status, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. As a Federal Contractor, UTMB Health takes affirmative action to hire and advance protected veterans and individuals with disabilities. Compensation