The Nuclear Science and Engineering (NSE) Division is seeking a postdoctoral appointee to develop computational methods and computer codes to model the physics and engineering of advanced nuclear reactors; analyze the multi-physics aspects of nuclear fission/fusion reactors including neutronics, thermal-hydraulics, structural mechanics, and fuel behavior. Activities may involve reactor analysis including transient analysis, engineered system evaluation, and machine learning applications in modeling thermal fluid behavior of interest to reactor analysis. The candidate is expected to produce papers and reports describing results of development work, analyses, and investigations. **Position Requirements** + Knowledge of nuclear engineering principles, theories, and practices for the design and analysis of reactor systems. + Knowledge of heat transfer and fluid dynamics for nuclear system applications and reactor safety analyses. + Knowledge of computation methods and numerical solvers for engineering applications. + Knowledge of modern software development practices and programming techniques. + Skills in the use of computers and in the analysis of computational results, in the clear and effective documentation and communication of results, and in interaction with co-workers and support personnel is required. + Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. + Ability to make our laboratory a safe, welcoming, inclusive, and accessible environment where all can thrive. Minimum Education and Experience Requirements: This level of knowledge is typically achieved through a formal education in Nuclear Engineering, Physics, or a related field at the PhD level with zero to five years of employment experience. **Preferred Knowledge, Skills, and Experience** + Knowledge of reactor transient and accident analysis methods and experience in using system codes (e.g. RELAP5, TRACE, SAM, or SAS4A/SASSYS-1). + Knowledge of the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. + Experience in computational modeling of advanced reactor designs including both fission and fusion systems. + Knowledge of machine learning algorithms and experience in machine learning applications related to thermal fluid problems and/or nuclear reactor analysis. **Job Family** Postdoctoral Family **Job Profile** Postdoctoral Appointee **Worker Type** Long-Term (Fixed Term) **Time Type** Full time _As an equal employment opportunity and affirmative action employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne encourages minorities, women, veterans and individuals with disabilities to apply for employment. Argonne considers all qualified applicants for employment without regard to age, ancestry, citizenship status, color, disability, gender, gender identity, gender expression, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law._ _Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department._ _All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment._