Open to opportunities

Luke Shaw

@lukeshaw

Message

PhD applied mathematician specializing in probabilistic modelling and ML systems.

Spain

Message

What I'm looking for

I seek research-driven roles combining applied mathematics and ML, with opportunities to build production software, publish research, and collaborate internationally.

I hold a PhD in applied mathematics with strong experience in Hamiltonian Monte Carlo, generative diffusion models, and stochastic methods, combined with commercial software development and embedded systems cybersecurity.

My academic training includes an MSc in Computational Applied Mathematics (University of Edinburgh) and a BSc in Physics (Princeton University). I have authored seven research articles and completed international research stays in Edinburgh and Guatemala.

On the engineering side, I develop open-source software in Python and C/C++ (FastAPI, CI/CD via GitHub Actions), build cross-platform tools, and produce technical audiovisual content to promote projects. I have practical experience with TensorFlow, PyTorch, Keras, and computer vision workflows.

I bring a blend of rigorous mathematical modelling, machine/deep learning expertise, and hands-on software engineering to tackle inverse problems, Bayesian inference, and production ML systems.

Experience

Work history, roles, and key accomplishments

Current

Software Engineer

Current

ironArray SLU

Mar 2025 - Present (10 months)

Developed open-source cross-platform software packages in Python (FastAPI) and C/C++, implemented GitHub CI/CD pipelines, and produced audiovisual content that increased project visibility (repositories totalling 2.4K stars).

Python fastAPI C C++Git Github CI CD Cross Platform Development CMake Linux

Postdoctoral Researcher

Universitat Jaume I

Nov 2024 - Mar 2025 (4 months)

Conducted postdoctoral research in applied mathematics focusing on Hamiltonian Monte Carlo and generative diffusion models using PyTorch, contributing to peer-reviewed publications and collaborative international stays.

PyTorch Stochastic Methods Publications Numerical Methods Hamiltonian Monte Carlo Generative Models

Doctoral Researcher

Universitat Jaume I

Oct 2021 - Oct 2024 (3 years)

Led doctoral research in applied mathematics producing seven articles on Hamiltonian Monte Carlo, diffusion models and stochastic gradient methods, and completed research visits to Edinburgh and Guatemala.

Hamiltonian Monte Carlo Diffusion Models PyTorch Stochastic Gradient Methods Scientific Writing

Cybersecurity Researcher

IKERLAN

May 2020 - Aug 2020 (3 months)

Developed TensorFlow 2.0 code for neural network attribution (e.g., LRP) applied to side-channel analysis for symmetric cryptography as part of an industrial MSc thesis.

TensorFlow Layer Wise Relevance Propagation Embedded Systems Python Cryptography

Computer Vision Intern

Institute of Complex Systems

Jun 2018 - Aug 2018 (2 months)

Extended a MATLAB codebase for automated analysis of fish trajectories to support behavioral research and large-scale data processing.

Matlab Computer Vision Data Processing Algorithm Development

Quantum Computing Researcher

Princeton University

Jun 2016 - Apr 2017 (10 months)

Researched and simulated 3D microwave cavities for qubit control, machined cavity components, and operated SEM equipment to support experimental quantum computing efforts.

Quantum Computing Machining SEM Experimental Physics Matlab

Education

Degrees, certifications, and relevant coursework

Universitat Jaume I

Doctor of Philosophy, Applied Mathematics

2021 - 2024

Grade: sobresaliente, cum laude

Activities and societies: Authored research articles; research stays in Edinburgh and Guatemala.

PhD in Applied Mathematics with distinction (sobresaliente, cum laude), producing research on Hamiltonian Monte Carlo, generative diffusion models, and stochastic methods.