Postdoctoral Associate, Nuclear Science and Engineering

Working at MIT offers opportunities, an environment, a culture – and benefits – that just aren’t found together anywhere else. If you’re curious, motivated, want to be part of a unique community, and help shape the future – then take a look at this opportunity.

POSTDOCTORAL ASSOCIATE, Nuclear Science and Engineering (NSE) (2 openings), to apply advanced data analytics and machine learning to solve multidisciplinary and multiphysics design problems to make nuclear energy more economical.  Responsibilities include development of discrete optimization strategies (e.g., reinforcement learning-DQN/PPO, genetic algorithm, etc.) under uncertainty for various sectors of nuclear fission engineering including fuel, power plant structures, components and building, and overall plant site design.  Enabling efficient optimization under uncertainty, physics-informed machine learning (e.g., neural nets, tree based, GP, etc.) to represent different physics (e.g., radiation transport, thermal-fluids, structural mechanics) will be leveraged. Will work with Professor Koroush Shirvan of NSE as the direct supervisor and alongside team of researchers at NSE and the Concrete Sustainability Hub and the Quest for Intelligence.

Job Requirements

REQUIRED:  Ph.D. in nuclear engineering or mechanical engineering or civil engineering, or aerospace engineering or applied computer science. 

PREFERRED: experience with machine learning (classical and reinforced learning), optimization (e.g., genetic algorithm), uncertainty quantification (Bayesian frameworks), sensitivity analysis, high performance computing, engineering economics, computational fluid dynamics, and finite element analysis software. 

Job #18794