Harvard’s two-year MEng in Computational Science & Engineering equips engineers to craft parallel algorithms, multiphysics simulations, and data-driven digital twins. Students scale codes on the FAS Odyssey cluster, accelerate solvers on GPUs, and collaborate with NASA, NOAA, and biotech labs to predict climate extremes, optimize aerospace designs, or fold proteins in silico. A thesis-year residency embeds learners in sponsor labs, launching careers in national labs, Quant firms, and deep-tech startups.
GPU-accelerated CFD solver for hypersonic vehicles
Multiscale earthquake simulation coupling crust and city-building models
Agent-based pandemic spread model with real-time data assimilation
Quantum-inspired optimizer for portfolio risk minimization
Automatic differentiation library for physics-informed neural nets
Digital-twin pipeline monitoring offshore wind-farm fatigue
Finite-element model predicting 3-D-printed lattice strength
OpenFOAM extension for multiphase battery degradation
Climate-downscaling workflow on exascale architectures
Capstone on uncertainty quantification in fusion-reactor design
Visualization toolkit for billion-cell brain simulations
Elastic scaling of MPI jobs in Kubernetes clusters
Ethics brief on compute inequality in climate science
Hackathon developing fast solvers for groundwater contamination
Podcast interviewing CSE alumni at national supercomputing centers
Workshop teaching Julia for scientific machine learning
Benchmark suite for comparing graph-partitioning libraries
Interactive notebook demos for undergrad numerical-analysis courses
Simulate the future at scale with Harvard’s computational-science powerhouse.
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