Biomedical Digital Twin Factory Lead Technologist

The University of Texas at Austin•Austin, UT

17d•$60,000•Onsite

About The Position

The Biomedical Digital Twins Factory is a new, state-of-the-art facility for image analysis and model construction for medical digital twins. It supports the clinical research and educational mission of the Center for Computational Medicine - a collaboration between the Oden Institute and the Dell Medical School at The University of Texas at Austin. This position reports to Prof. Charles Taylor, the W.A. “Tex” Moncrief, Jr., Chair in Computational Medicine. The Oden Institute is an organized research unit that fosters interdisciplinary programs in computational sciences and engineering, computational medicine, computational geosciences, mathematical modeling, applied mathematics, data science, software engineering, and computational visualization. The University of Texas at Austin is a nationally ranked, tier-one research institution and one of the largest employers in central Texas. UT is located in the heart of Austin, a vibrant city that frequently appears on lists of best cities to live and work. Committed to recruiting and retaining a varied and talented workforce, the university offers competitive salaries and benefits, an extensive support network, and above all, an enriching and highly collaborative community that is deeply passionate about our vision for higher education and public service. UT Austin offers a competitive benefits package that includes: 100% employer-paid basic medical coverage Retirement contributions Paid vacation and sick time Paid holidays Please visit our Human Resources (HR) website to learn more about the total benefits offered. The Biomedical Digital Twin Factory Lead Technologist leads the core lab operations for developing and updating digital twins using 1) medical imaging (such as MRI and CT scans) and 2) multi-modal data (genomics and other physiological data). Digital twins are computer models based on anatomical and functional data, are updated in time with new information from imaging or physiologic data and can be used to predict risk for developing disease, response to potential therapies, or other physiological health and performance metrics. In this role, you will work with the research team, software developers, analyst staff, and graduate students in the implementation, documentation, and management of image and data processing. You will analyze data, draft and review work instructions and standard operating procedures, train other staff at UT as well as collaborators, and provide feedback regarding image and data processing pipelines.

Requirements

Bachelor's degree in a relevant field
Degree or formal training in 3D Modeling, 3D Animation, Medical Visualization, Computer Graphics, or a related discipline.
Visual and detail inspection skills
Adaptive, open learner, open to corrective feedback in image analyses
Ability to remain focused and consistent in analyzing images / data with standardized procedures
Motivated to produce high-quality work and perform with prolonged focus
Strong computer skills
3D computer skills
Excellent written and verbal communication
Proficiency in spreadsheet, slide, word processing and other tools
Relevant education and experience may be substituted as appropriate.

Nice To Haves

Experience with medical imaging
Experience with DICOM images

Responsibilities

Interact with medical imaging research workstation tools to extract anatomy and function data from 2D, 3D, and 4D data sets for the construction of personalized digital twins
Write instructions for as well as p erform standardized image and data quality checks to decode whether received image and other data match expected protocol and formats.
Provide written testing and feedback using screenshots on newly developed image and data analysis and clinical support tools
Interact with researchers and clinicians to understand image and data quality impacts, and implement in educational responsibilities
Lead 1-1 and small group demonstrations and trainings of lab pipelines, image quality, and image analysis tools, and document and track qualification and re-qualification