Postdoctoral Appointee in Scientific Machine Learning (Sandial National Labs)

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We are seeking a postdoctoral candidate interested in developing and applying novel machine learning methodologies for the purpose of scientific discovery of emergent epidemiological trends to support enhanced and accelerated pandemic response. Research will focus on developing explainable, data-driven models that can capture complex, multi-scale disease progression dynamics by combining scientific computing and machine learning subject areas (Scientific Machine Learning). The work will be performed with an interdisciplinary research team with research strengths in computational mathematics, computational science, high performance computing, scientific software development, uncertainty quantification, and machine learning algorithms.

Applicants on this requisition may be interviewed by multiple organizations at Sandia National Laboratories.

The selected applicant can be a virtual worker located in any U.S. State or District of Columbia. Regular or periodic travel to your assigned work location may be required.


  • Possess, or are pursuing, a PhD in computational science, computer science, applied mathematics, statistics, data science, or a related engineering or science field
  • Research experience in one or more of the following areas: differential equations, optimization, scientific machine learning, complex systems, epidemiological models, probability theory, uncertainty quantification, or other relevant areas


  • Strong written and oral communication and interpersonal skills
  • Ability to work on a team to solving complex interdisciplinary R&D problems relevant to DOE missions.
  • Familiarity with compartmental models (i.e., ordinary differential equations), neural networks as universal approximators, spatial diffusion modeling.
  • A dedication to encouraging an inclusive R&D environment, as proven in your application materials.
  • Background in solving practical problems in science and engineering that involve real world data.
  • Research community leadership through activities such as participation in student or professional organizations, service on committees, workshop and/or conference organization, and editorial roles.


The mission of the Scientific Machine Learning Department at Sandia National Laboratories is to provide leadership in the research, development, and application of artificial intelligence and machine learning to scientific and engineering problems. The department is well known for research contributions in inverse modeling, design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis. Key customers include the NNSA Advanced Simulation Computing program, the Office of Science, and the broader Sandia missions in Nuclear Deterrence. The department frequently hosts students and faculty from world-class universities for extended visits through the Computer Science Research Institute (CSRI; see

Our team is committed to nurturing environment compatible with a broad group of people and perspectives in accordance with the changing makeup of the workforce. In support of this vision, our center actively recruits applicants from diverse groups of backgrounds and fosters an inclusive community.Join us and work towards your goals while making a difference!

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