Internship: Multiphysics simulation and optimization

Cambridge, Massachusetts, United States · BI · 1163


MERL is seeking a motivated graduate student to research numerical methods related to model-based simulation and optimization for process applications. Representative targets include the fast simulation of multiphase flows and the optimization of nonsmooth systems found in energy applications. The ideal candidate would have a solid background in numerical methods, partial differential equations, and optimization; strong programming skills and experience with Python/C++/Matlab are also expected. Knowledge of the fundamental physics of thermofluid flows (e.g., thermodynamics, heat transfer, and fluid mechanics), nonlinear dynamics and control methods, or Modelica or other equation-oriented languages (gPROMS, Aspen HYSYS, extensions to Julia such as JuMP.jl) is a plus. The expected duration of this internship is 3 months. Please contact Chris Laughman (laughman at or go to for more information.

Research Area: Business Innovation

Contact: Chris Laughman

Apply for this job