Research Scientist II - Health and Clinical Outcomes Research na UTMB Health

%3Cp class=%22MsoNoSpacing%22%3E%3Cspan style=%22font-family:%26quot;Arial%26quot;,sans-serif;font-size:14px;%22%3E%3Ci%3E%3Cstrong%3EDEPT MARKETING STATEMENT:%3Co:p%3E%3C/o:p%3E%3C/strong%3E%3C/i%3E%3C/span%3E%3C/p%3E%3Cp%3E%3Cspan style=%22color:black;font-family:%26quot;Arial%26quot;,sans-serif;font-size:14px;%22%3E%3Cspan style=%22line-height:115%;mso-ansi-language:EN-US;mso-bidi-language:AR-SA;mso-fareast-font-family:Aptos;mso-fareast-language:EN-US;mso-fareast-theme-font:minor-latin;%22%3EUTMB’s new Center for Health and Clinical Outcomes Research (H-COR) seeks %3Cstrong%3EResearch Scientists%3C/strong%3E 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 schools%3C/span%3E%3C/span%3E%3C/p%3E%3Cp%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3E%3Cstrong%3EJOB DESCRIPTION:%3C/strong%3E %26nbsp;%26nbsp;%26nbsp;%26nbsp;%3C/span%3E%3Cbr%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3EConducts 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.%26nbsp;%3C/span%3E%3C/p%3E%3Cp%3E%3Cbr%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3E%3Cstrong%3EESSENTIAL JOB FUNCTIONS:%3C/strong%3E%3C/span%3E%3C/p%3E%3Cul%3E%3Cli%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3ELeading and contributing to high-impact health and clinical outcomes research%26nbsp;%3C/span%3E%3C/li%3E%3Cli%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3EPlanning and performing advanced data analyses using UTMB%27s exceptional data infrastructure, with particular emphasis on electronic health record (EHR) data including EPIC, EPIC Cosmos, TriNetX, and Medicare administrative datasets%3C/span%3E%3C/li%3E%3Cli%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3EBuilding transparent cohort definitions and phenotypes using ICD-10/PCS, CPT/HCPCS, LOINC, and RxNorm%3C/span%3E%3C/li%3E%3Cli%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3EImplementing 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)%3C/span%3E%3C/li%3E%3Cli%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3ECollaborating across UTMB’s schools on defined research programs%3C/span%3E%3C/li%3E%3Cli%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3EContributing to abstracts, manuscripts, and grant applications as PI/Co-I or key personnel%3C/span%3E%3C/li%3E%3Cli%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3EIntegrating clinical timelines with multi-omics and other high-dimensional data while preserving clinical interpretability and privacy%3C/span%3E%3C/li%3E%3Cli%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3EPresenting research at professional meetings and conferences%3C/span%3E%3C/li%3E%3Cli%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3EParticipating in H-COR%27s monthly works-in-progress seminars%3C/span%3E%3C/li%3E%3C/ul%3E%3Cp%3E%3Cbr%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3E%3Cstrong%3EMINIMUM QUALIFICATIONS:%3C/strong%3E%3C/span%3E%3Cbr%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3EPh. D, M.D, D.O., or D.V.M in related field and one year of related experience.%3C/span%3E%3C/p%3E%3Cp%3E%3Cbr%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3E%3Cstrong%3EPREFERRED QUALIFICATIONS:%26nbsp;%3C/strong%3E%3C/span%3E%3C/p%3E%3Cul%3E%3Cli%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3EPhD or equivalent doctoral degree in a relevant discipline (health services research, epidemiology, biostatistics, data science, computer science, or a closely related field)%26nbsp;%3C/span%3E%3C/li%3E%3Cli%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3EA track record in health and clinical outcomes methods%26nbsp;%3C/span%3E%3C/li%3E%3Cli%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3EDemonstrated expertise analyzing clinical and population-health data with specific experience in EHR analytics%26nbsp;%3C/span%3E%3C/li%3E%3Cli%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3EProficiency with large healthcare databases (Epic, Epic Cosmos, TriNetX, Medicare)%26nbsp;%3C/span%3E%3C/li%3E%3Cli%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3EFluency in at least two of R, Python, SAS, and SQL%26nbsp;%3C/span%3E%3C/li%3E%3Cli%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3EExcellent scientific writing and communication%26nbsp;%3C/span%3E%3C/li%3E%3Cli%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3EEvidence of peer-reviewed publications commensurate with career stage%26nbsp;%3C/span%3E%3C/li%3E%3Cli%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3EExperience with OMOP and HL7 FHIR data models%26nbsp;%3C/span%3E%3C/li%3E%3Cli%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3EHands-on practice with target-trial emulation and advanced propensity and longitudinal methods%26nbsp;%3C/span%3E%3C/li%3E%3Cli%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3EClinically oriented NLP and time-aware feature extraction%26nbsp;%3C/span%3E%3C/li%3E%3Cli%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3EFamiliarity with multi-omics data structures and cautious EHR-omics linkage%3C/span%3E%3C/li%3E%3Cli%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3EExperience in HPC or cloud settings (e.g., TACC, Azure, AWS) and workflow engines that promote end-to-end reproducibility%26nbsp;%3C/span%3E%3C/li%3E%3Cli%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3EMentorship of analysts or trainees%26nbsp;%3C/span%3E%3C/li%3E%3Cli%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3EA record of effective, cross-disciplinary collaboration in an academic health-sciences environment%3C/span%3E%3C/li%3E%3C/ul%3E%3Cp%3E%3Cbr%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3E%3Cstrong%3ESALARY:%3C/strong%3E%3C/span%3E%3Cbr%3E%3Cspan style=%22font-family:Arial, Helvetica, sans-serif;font-size:14px;%22%3ECommensurate with experience.%26nbsp;%3C/span%3E%3C/p%3E

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.

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