Postdoctoral Scholar-Fixed Term

MSU Careers Details • East Lansing, MI

4d

About The Position

The Postdoctoral Scholar will conduct research within the Nuclear Theory Group, developing and applying microscopic transport models and modern statistical and artificial intelligence/machine learning (AI/ML) methods to constrain the properties of dense nuclear matter using heavy-ion collision data. The work includes improving transport approaches, particularly the SMASH transport model, and applying computational methods to experimental programs at FRIB, STAR FXT, HADES, CBM, and related facilities.

The scholar will participate in Group research activities, mentor graduate and undergraduate students, and disseminate results through publications, conferences, and workshops. Other duties may be assigned when reasonably within the scope of the position.

Requirements

• Ph.D. in Nuclear Physics or a related field, or anticipated Ph.D. completion by Summer 2027.
• At least one year of demonstrated research experience in at least one of the following: developing microscopic transport simulations, particularly BUU-based approaches; Bayesian analysis or statistical inference involving dynamical or computationally intensive models; or developing or applying AI/ML methods in computational science.
• Ability to carry out independent and original research, demonstrated through published works in refereed journals and/or conference proceedings.
• Demonstrated written and oral communication skills, evidenced by published works and presentations at conferences, workshops, scientific outreach, or other professional meetings.
• Ability to work with export-controlled technologies.
• Strong background in nuclear theory and computational physics.
• Skill and experience in at least one of these areas: developing and applying microscopic transport models for heavy-ion collisions, particularly BUU approaches; Bayesian inference and parameter estimation for computationally intensive dynamical simulations; or developing and applying AI/ML methods to scientific modeling and data analysis.
• Scientific programming ability, particularly in C++ and/or Python, and familiarity with high-performance computing environments.
• Ability to develop, validate, and interpret computational models.
• Ability to conduct independent research while contributing effectively to collaborative projects.
• Ability and willingness to mentor students and contribute to their scientific development.
• Strong written and verbal communication skills, including presenting research results clearly to scientific audiences through publications and presentations.

Nice To Haves

• Experience with the SMASH transport model or other microscopic transport approaches used in heavy-ion physics.
• Familiarity with dense nuclear matter physics and heavy-ion collisions at low and intermediate relativistic energies.
• Experience with Bayesian parameter estimation, uncertainty quantification, or surrogate modeling.
• Experience applying machine learning methods to physical simulations or scientific data analysis.
• Experience mentoring or supervising students in research activities.

Responsibilities

• Develop and improve microscopic transport approaches, particularly the SMASH transport model, to investigate dense nuclear matter probed in heavy-ion collisions.
• Develop and apply computational and statistical methods, including Bayesian inference and AI/ML, to improve transport simulations, accelerate computational workflows, and extract nuclear matter properties through quantitative comparisons with experimental measurements.
• Participate actively in the Nuclear Theory Group’s research activities.
• Mentor graduate and undergraduate students in their research projects.
• Disseminate research results through publications, conferences, and workshops.
• Perform other duties as required or assigned that are reasonably within the scope of the job classification.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree