We offer several research internship pathways, including machine learning, quantitative research and, in some years, a dedicated natural language processing track. The exact projects available can vary depending on our research priorities and mentors each year, but expertise in NLP, language modelling and LLMs is relevant across a much broader range of teams and research problems at G-Research.
Whichever route you take, you’ll be thrown into work that matters, with close mentorship, serious technical challenge and exposure to the kind of problems that define research at G-Research.
Machine learning research internship
If it worked reliably at scale, someone would’ve built it already. Your summer ML internship is spent on problems that don’t have GitHub solutions: models that need to predict market behaviour with incomplete information and systems that need to train on data volumes that break standard approaches. You’ll strengthen your understanding of deep learning frameworks, learn best practices and gain experience communicating your findings clearly through documentation and scientific writing.
The mentorship and support is unrivalled, it’s there to provide you with tangible advice to go into your career, where your code will be reviewed by people who’ve shipped ML production systems and experimental design is challenged by researchers who can spot flaws and suggest next steps.
The ones who thrive here are the people who get obsessed with why something doesn’t work yet. Who read ML papers not just to implement them but to understand their limitations. Who want their summer measured by what they built, not just what they learned.
Quantitative research internship
Our quantitative research internship drops you straight into real research. You’ll use advanced mathematics, statistics and computational tools to tackle the kind of analytical challenges that shape our long-term strategies.
Expect to build and test statistical models, run simulations, uncover hidden patterns in complex datasets and explore ideas that push beyond conventional approaches. Along the way, you’ll sharpen your expertise in probability, optimisation and Python-based data workflows, and develop the rigorous research mindset that defines world-class quant work.
This programme is built for candidates with serious quantitative talent – people who think in equations, question assumptions and enjoy understanding complex systems through data. If you want to apply your skills at the highest level, this is your proving ground.
Natural language processing (NLP) internship
Our NLP internship gives you 10 weeks inside an applied research environment where large language models, large-scale text data and quantitative research meet. You’ll work on a meaningful project that calls for mathematical talent, pragmatic computational thinking and the ability to build beyond off-the-shelf methods.
LLM expertise is increasingly relevant well beyond dedicated NLP projects, with language modelling techniques applicable across a range of research teams and problems. Experience experimenting with, evaluating or building around LLMs can therefore be particularly valuable.
You’ll be paired with a mentor, receive regular feedback from experienced researchers and finish the programme by presenting your ideas to senior leaders. This track is best suited to candidates with postgraduate study or strong experience in NLP, machine learning, LLMs or a related discipline, plus strong Python skills and experience with frameworks such as PyTorch or TensorFlow.
