Numerical & Mathematical
Numerical PDEs, finite element methods, pseudo-spectral methods, variational methods, functional analysis, inverse problems, PDE-constrained optimisation, Tikhonov/variational regularisation, reduced-order modelling (POD-Galerkin), hyper-reduction (DEIM), Bayesian inference (MCMC/pCN), ensemble data assimilation, dynamical systems.
Scientific ML / ML
PyTorch, TensorFlow, scikit-learn, physics-informed neural networks (PINNs), Fourier Neural Operators, surrogate/operator learning, computer vision, time series, classification, anomaly detection.
Scientific Computing
Python, NumPy, SciPy, MATLAB, C++, FEniCSx, PETSc, JAX, FFT-based computing, LaTeX.
Engineering
SQL, IBM DB2, PostgreSQL, FastAPI, Docker, Git, REST APIs, ETL/data pipelines, AWS.
Applied ML & Generative AI
RAG, LoRA, QLoRA, Hugging Face, LangChain, LangSmith, differentiable computing, neural rendering, medical imaging.