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University of Minnesota

Postdoctoral Associate in Mathematical Foundations of Generative AI

Closes:

Salary: $69,000 per hour

67


About the Job

About the Position

The School of Mathematics at the University of Minnesota Twin Cities invites applications for a postdoctoral position. Candidates are expected to have received a Ph.D. in Mathematics, Statistics, or a closely related field by the start of the appointment. The anticipated start date is summer 2027, with the possibility of an earlier start by mutual agreement. The initial appointment is for two years, with the possibility of renewal for a third year, subject to satisfactory performance and the availability of funding.

The successful candidate will work with Dr. Yulong Lu on research projects related to the mathematical and computational foundations of generative artificial intelligence. Potential research topics include the mathematical and statistical analysis of modern generative models, particularly diffusion- and flow-based models, as well as their applications to scientific computing and other scientific domains. Candidates with strong backgrounds in stochastic analysis, numerical analysis, sampling methods, optimization, scientific computing, or related areas, together with research experience in at least one class of modern generative models, are particularly encouraged to apply. In addition to conducting research, the successful candidate will teach two courses per year. The position is supported by the National Science Foundation (NSF) and the University of Minnesota and will provide opportunities for collaboration with mathematicians and computer scientists at Duke University and Yale University.

Employment Requirements: Any offer of employment is contingent upon the successful completion of a background check. Our presumption is that prospective employees are eligible to work here. Criminal convictions do not automatically disqualify finalists from employment.

Qualifications

Required Qualifications:
  • Ph.D. in Mathematics, Statistics, or a closely related field by the start of the appointment.

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