🔬 Computational Physicist | ⚡ Quantum Modelling | 📊 Data Scientist
📧 rjones@turing.ac.uk | robert.m.jones@kcl.ac.uk | KCL Profile | ORCID
Deep expertise at the intersection of ultrafast phenomena, condensed matter physics, and large-scale data science. Currently leveraging Machine Learning to accelerate quantum chemistry simulations, model complex physical systems, and extract insights from high-dimensional datasets.
🔷 Sapphire - Multi-faceted platform for designing, characterising, and computing dynamics/energetics of metallic nanoparticles. (Computational Physics/Quantum Dynamics)
📰 News-NLP - PyTorch Natural Language Processing on synthetic and ethically web-scraped data for characterising news article headlines. (Machine Learning/NLP)
📉 Streamdash - StreamLit and YFinance python-based GUI for analysing stock and ETF prices based on historical and live data. (Data Engineering/Financial Analysis)
Data Scientist | The Alan Turing Institute (2025–Present)
- Applying advanced machine learning and statistical modeling to high-impact research challenges.
- Developing robust, scalable AI solutions using high-performance computing (HPC) environments.
- Collaborating with domain experts to translate complex theoretical models into practical data workflows.
Postdoctoral Research Associate | King's College London (2023–2025)
- Lead researcher on chiral light-matter interactions, condensed matter physics, nonlinear light-matter interactions.
- Developed computational frameworks and ML tools for quantum chemistry prediction.
Core: Python (PyTorch/TensorFlow), Fortran, C, C++ HPC: MPI, CUDA, OpenMP, Distributed Computing Tools: UNIX/Bash, SQL, Docker/Containerization, LaTeX, Mathematica
PhD Physics | King's College London (2019–2022) MSc Non-Equilibrium Systems | KCL (2018–2019) MPhys Theoretical Physics | University of Leeds (2014–2018)
- Multiple peer-reviewed publications in leading journals and high-profile conference proceedings.
- Development of production-grade computational and machine learning frameworks.
- Experience in student research supervision and publication.
🌍 Languages: English (native), Italian (conversational), French (intermediate), German (beginner)