Conduct applied research in AI, ML, and Modeling and Simulation for healthcare, with a focus on multimodal analytics, time-series analysis, and utilizing statistical methods for domain-specific impact.
Lead the development of novel AI methods applied to biomedical challenges, collaborating with scientists across ACH/CSED in data analytics and architecture research.
Author peer-reviewed papers, technical reports, and proposals, and represent ORNL through technical presentations at large public forums.
Develop, optimize, and transition algorithm prototypes into robust implementations based on project requirements.
Collaborate with CCSD researchers, internal teams, and external sponsors to understand and integrate requirements into algorithm and software development.
Interpret, report, and present research findings at national forums, and maintain a strong scientific publication profile.
Contribute to ORNL’s mission by promoting diversity, equity, inclusion, and accessibility, aligning with core values such as Impact, Integrity, Teamwork, Safety, and Service.
Engage in cutting-edge research using ORNL’s Leadership Class Supercomputer in a dynamic, collaborative research environment.
Maintain membership in relevant professional, academic, and research organizations.
Requirements & Skills:
PhD in Computer Science, Mathematics, Computational Sciences, or a related engineering field.
A minimum of 5 years of experience in biomedical and health applications.
Proven expertise in working with big data, a strong publication record, and experience in building information systems that support the discovery of scientific insights for Multiscale Biomedical Systems.
Experience conducting fundamental and applied research on biomedical and healthcare data, with a focus on AI, ML, Modeling and Simulation, and High-Performance Computing.
Ability to devise and implement innovative solutions for nationally significant issues, with proven R&D execution to bring these solutions into practical use.
Proven experience collaborating with biomedical researchers, internal teams, and external sponsors to incorporate requirements into algorithms and software solutions.
Experience in big data, streaming data platforms, high-performance computing, and modeling and simulation.
Proficiency in machine learning/deep learning programming and applications in biomedical data, with a preferred background in natural language processing.
Hands-on experience working with electronic health record (EHR) data and strong publication records in areas such as healthcare data science, modeling and simulation, and high-performance computing
Proven research ability, demonstrated by a strong publication record, participation in professional associations, and the ability to produce significant research results.
Expertise in data integration technologies and core semantic technologies (RDF, OWL, SPARQL).
Strong written and oral communication skills.
Motivated self-starter with the ability to work independently, and collaboratively, and adapt to changing research needs in a fast-paced environment.
Proficiency in programming (e.g., Java, Python, C/C++) and flexibility in research assignments.
Demonstrated ability to collaborate effectively with scientists, engineers, and sponsors, and contribute to funding proposals.
