Northwestern’s Applied Mathematics PhD tackles problems from turbulence control to financial risk via advanced analysis, stochastic calculus, and high-performance computing. Students join interdisciplinary centers—bio-logic networks, quantum materials, and climate modeling—publishing in SIAM and Nature partner journals. A professional-development series prepares graduates for academia, industry research labs, and quantitative finance leadership.
Derive and simulate reduced-order models for atmospheric gravity waves
Develop stochastic control frameworks for pandemic intervention policies
Analyze mean-field games in electric-vehicle charging networks
Prove long-time stability of energy-conserving finite-element schemes
Design GPU-accelerated solvers for incompressible Navier–Stokes at high Re
Model systemic financial contagion using interacting particle systems
Investigate multi-scale homogenization in composite battery electrodes
Prove existence of solutions for nonlinear dispersive PDEs with fractional damping
Create neural operator surrogates for seismic inversion problems
Study knot invariants in fluid vortex reconnection dynamics
Optimize vaccine allocation via stochastic differential variational inequalities
Apply optimal-transport to fairness constraints in machine-learning pipelines
Compute spectral gaps in quantum graph models of photonic crystals
Formulate game-theoretic models for adaptive cyber-defense strategies
Write an expository survey on rough-path theory applications to finance
Advance mathematical frontiers and interdisciplinary discovery with Northwestern’s PhD.
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