Director - Scientific AI R&D

Oak Ridge National LaboratoryOak Ridge, TN

About The Position

Oak Ridge National Laboratory (ORNL) is seeking a visionary Director of AI Foundations for Science to lead the laboratory’s strategic direction and execution at the intersection of artificial intelligence, high-performance computing, and scientific discovery. As the Department of Energy’s largest science and energy laboratory, ORNL delivers breakthrough capabilities in computing, neutron science, materials, energy, and national security. This role will define and drive the next generation of AI-enabled scientific discovery, building on ORNL’s leadership in exascale computing and emerging sovereign AI infrastructure for science. This position will report to the Associate Lab Director of Computing and Computational Sciences Directorate and will play a central role in shaping laboratory-wide and national strategies for AI-driven science and engineering.

Requirements

  • Ph.D. in a relevant STEM discipline, including but not limited to Computer Science, Applied Mathematics, Engineering, or a related field.
  • 15+ years of experience beyond Ph.D. in AI, computational science, or related fields
  • Demonstrated leadership of large-scale R&D programs and multidisciplinary teams
  • Internationally recognized expertise in one or more areas: Machine learning / AI, Scientific computing / HPC, Data-intensive science
  • Strong track record of securing and managing major research programs or partnerships

Nice To Haves

  • Experience operating at the intersection of AI, HPC, and scientific domains (e.g., materials, biology, energy, physics)
  • Proven ability to build public-private partnerships at scale
  • Experience with DOE, national laboratory, or comparable mission-driven environments
  • Vision for AI-driven transformation of science and engineering workflows
  • Demonstrated success influencing national or institutional strategy

Responsibilities

  • Define and execute ORNL’s strategy for AI as a foundational scientific capability, focusing on the co-evolution of algorithms, models, data, and computing architectures.
  • Establish R&D priorities across: AI foundation models trained on scientific and simulation data at scale, Mathematical foundations of scientific AI, Physics-informed and hybrid AI (AI + simulation + experimental data fusion), AI-HPC co-design, including new programming models and system architectures.
  • Serve as the laboratory’s focal point for AI innovation at the frontier of computation, enabling downstream application domains (energy, security, materials, biology) through shared capabilities and platforms.
  • Partner with other ORNL leaders to advance agentic and autonomous discovery systems tightly coupled to instruments and facilities, advance data-centric and multimodal AI pipelines for scientific workflows, and drive integration of AI into major user facilities, instruments, and simulation environments.
  • Position ORNL as the global leader in integrated AI + HPC + experimental science ecosystems.
  • Lead and grow world-class, multidisciplinary R&D programs spanning computational science, applied AI, and domain science.
  • Shape and advance a research portfolio that integrates foundational applied mathematics, computer science, and trustworthy AI to support scientific AI and computational discovery.
  • Identify and scale high-impact flagship initiatives demonstrating end-to-end AI-enabled scientific workflows.
  • Build and lead strategic partnerships with industry (hyperscalers, AI companies, semiconductor firms), Universities and academic consortia, and Other DOE laboratories and federal agencies.
  • Expand industrial engagement and co-development programs, including joint AI platforms and applied science use cases.
  • Represent ORNL in national and international AI strategy forums.
  • Work in close partnership with AI and autonomous science leaders across ORNL scientific domains, Applied Energy Sciences and National Security to translate foundational AI advances into mission impact, while maintaining a clear separation between capability creation and mission deployment.
  • Drive modernization of scientific workflows through AI-native software ecosystems, Data-centric architectures and platforms, and Agentic and autonomous laboratory capabilities.
  • Support ORNL in adoption of AI to transform laboratory operations, including proposal development, safety, and facility optimization.
  • Advance ORNL toward a fully integrated physical–digital laboratory model.
  • Build, mentor, and lead high-performing teams across AI, computing, and domain science.
  • Foster a culture of mission impact, collaboration, and urgency in a rapidly evolving global landscape.
  • Partner across directorates to ensure cross-cutting integration of AI capabilities.

Benefits

  • Home to leadership-class computing and emerging AI infrastructure
  • Unmatched integration of experimental facilities, computing, and data ecosystems
  • Mission-driven environment addressing the nation’s most critical challenges
  • Opportunity to define the future of AI-enabled science at national scale
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