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The Division of Cardiovascular Medicine at the University of Virginia seeks a Research Scientist to join the Cardiac Imaging research program led by Amit R. Patel, MD, Julian Ruffin Beckwith Professor of Medicine and Radiology and Director of Cardiac Imaging.\n \nThe Cardiac Imaging research program applies novel multimodality imaging tools - echocardiography, cardiac magnetic resonance (CMR), cardiac computed tomography, and nuclear cardiology - to clinically challenging problems in cardiovascular medicine. Active areas of investigation include quantitative assessment of chamber size and function, myocardial strain and deformation imaging, myocardial perfusion and blood flow quantification, characterization of epicardial adipose tissue, and improved detection and risk stratification of infiltrative and inflammatory cardiomyopathies including cardiac amyloidosis and cardiac sarcoidosis.\n \nThe program collaborates extensively with biomedical engineers, computer scientists, and radiologists at UVA, and participates in multicenter and international consortia as well as industry-sponsored studies.\n \nResearch Scientists are expected to perform assigned tasks independently. In addition to a firm background in the particular field, Research Scientists should demonstrate the ability to lead small groups and work without additional supervision once objectives are defined and methods of approach are set.\n \nPrimary responsibilities include:\n\n Independently designing, executing, and managing clinical and translational cardiovascular imaging research studies, including protocol development, IRB submission and maintenance, and regulatory documentation.\n Performing and overseeing quantitative image analysis for research purposes, including two- and three-dimensional chamber quantification, volumetric analysis, speckle-tracking strain and deformation analysis, diastolic function assessment, and tissue characterization across imaging modalities.\n Developing, documenting, and standardizing image acquisition and measurement methodology for multicenter studies; training and quality-assuring other analysts and participating site personnel; maintaining measurement reproducibility standards.\n Serving in a core-laboratory capacity for single-center, multicenter, and international imaging studies and registries.\n Building and maintaining imaging research databases and registries; ensuring data integrity, provenance, and compliance with institutional and sponsor requirements.\n Contributing to the validation and clinical evaluation of automated and artificial intelligence-based image analysis tools developed with engineering and industry collaborators.\n Conducting statistical analysis and interpretation of study results, including outcomes analysis and development of risk prediction models.\n Preparing manuscripts, abstracts, presentations, and grant application materials; serving as first or contributing author on peer-reviewed publications.\n Coordinating with internal and external collaborators, including multicenter site investigators, imaging core laboratories, professional societies, and industry partners.\n Providing day-to-day scientific direction to research coordinators, analysts, and trainees assigned to program projects.\n \nIn addition to the above job responsibilities, other duties may be assigned.\n \nQUALIFICATIONS\n \nRequires a doctoral degree (PhD or MD) or foreign equivalent degree in medicine, biomedical engineering, medical physics, or a closely related field. A master's degree with significant experience may also be considered. Candidates must have demonstrated experience conducting cardiovascular imaging research, including hands-on quantitative analysis of cardiac imaging data, and a record of peer-reviewed publication in cardiovascular imaging or a related discipline. Demonstrated ability to work independently and to carry research projects through to completion is required.\n \nPreferred Qualifications\n\n Deep, hands-on expertise in quantitative echocardiographic and cardiac magnetic resonance analysis, including three-dimensional volumetric quantification of the cardiac chambers, speckle-tracking strain analysis, and quantitative assessment of atrial and right ventricular size, systolic function, and diastolic function.\n Demonstrated responsibility for methodology development within a multicenter or international imaging study.\n Experience performing high-volume, protocol-driven image analysis in a core laboratory or equivalent setting, with documented attention to measurement reproducibility and inter-observer variability.\n Experience validating automated or artificial intelligence based cardiac image analysis tools against manual reference measurements, including collaboration with software developers or industry partners.\n Research experience in infiltrative or inflammatory cardiomyopathy, particularly cardiac amyloidosis to include including imaging-based diagnosis, phenotyping, and association of imaging findings with clinical outcomes.\n Experience with novel image post-processing and display techniques in echocardiography and cardiac magnetic resonance to include advanced three-dimensional rendering, feature-tracking strain analysis, parametric mapping, and quantitative tissue characterization.\n Formal training in clinical research methodology, epidemiology, or biostatistics (e.g., a master's degree or equivalent), with experience in outcomes analysis and the development or external validation of clinical risk prediction models.\n Proficiency with vendor and research image analysis platforms (e.g., TomTec, EchoPAC, QLAB, or equivalent) and with statistical software (e.g., R, SPSS, SAS, Stata, or Python).\n Familiarity with multimodality cardiac imaging (CMR, cardiac CT, and/or nuclear imaging) in a research setting, or a demonstrated interest in extending expertise across modalities.\n Experience with IRB protocols, human subjects research regulatory requirements, and clinical research data management.\n A substantial record of first-author peer-reviewed publications and abstracts presented at national or international cardiovascular imaging meetings, together with active engagement in professional imaging societies.\n Experience working within international, multi-institutional research collaborations; proficiency in an additional language is an asset.\n \nPHYSICAL DEMANDS\n \nThis is primarily a sedentary job involving extensive use of desktop computers. The job does occasionally require traveling some distance to attend meetings, and programs.\n \nSalary will be commensurate with education and experience.\n \nThis is an exempt-level, benefited position. Learn more about UVA benefits .\n \nInitial appointments and reappointments to these positions may be made in increments of one to three years, contingent upon satisfactory performance and the availability of funding. This position is based in Charlottesville, VA, and must be performed fully on-site.\n \nAbout UVA and the Community\n \nTo learn more about UVA and in the Charlottesville area, visit UVA Life and Embark CVA .\n \nAdditional Requirements \n \nBackground checks and pre-employment health screenings will be conducted on all new hires prior to employment.\n \nHow to Apply \n \nPlease apply online , by searching for requisition number R0086456. Complete an application with the following documents: \n\n Resume \n Cover Letter\n* Contact information for three professional references\n \nUpload all materials into the resume submission field. You can submit multiple documents into this one field or combine them into one PDF. Applications without all required documents will not receive full consideration.\n \nInternal applicants: Search and apply for jobs on the UVA Internal Careers website .\n \nContact\n \nFor questions about the application process, please contact Jeremy Brofft, Senior Academic Recruiter at xmf9ad@virginia.edu .\n \nThe University of Virginia is an equal opportunity employer. All interested persons are encouraged to apply, including veterans and individuals with disabilities. Learn more about UVA's commitment to non-discrimination and equal opportunity employment .