Quantitative Researcher PhD - 2027 Internship
Graviton Research Capital
Amsterdam, North Holland, Netherlands; London, England, United Kingdom; SingaporeonsiteentryinternshipToday
Graviton Research Capital
At Graviton, every strategy, model and edge begins not with instinct, but with someone asking a better question than everyone else. As a PhD Quantitative Research Intern, you'll spend 10-12 weeks pointing the research skills you've spent years building at markets. You'll collaborate with researchers and technologists to investigate market behaviour, test hypotheses, build predictive models and solve problems where the answers aren't obvious. This isn't an internship where you observe from the sidelines, or re-run someone else's experiment. Outstanding work has the potential to shape production strategies and generate real, measurable returns. Ideal candidates are researchers who want to see their methods meet live markets: mathematicians, physicists, statisticians and computer scientists who are excited to solve the hardest problems in our field, across our offices in the US, Singapore, Amsterdam and London. What You'll Work On You'll work on real research problems, not simulated exercises. Your work would include: Discovering predictive patterns from billions of market events Designing statistical models that identify trading opportunities Applying probability, optimization and machine learning to open research problems Running large-scale simulations and experiments on high-performance research infrastructure Designing experiments and backtests to evaluate hypotheses Building AI-powered research agents that accelerate experimentation Developing infrastructure for rapid, large-scale research Translating research into production-ready trading signals Exploring new ML, AI and quant finance techniques to find the next source of alpha What You'll Learn Beyond the technical exposure, you'll learn what changes when research meets live markets: why a result that would survive peer review can still fail as a trading signal, how costs and capacity constrain an idea that looks clean on paper, and how to tell a model that is right from one that is right for the wrong reason. You'll be paired with a mentor, reporting manager and buddy, with regular code reviews and feedback throughout the internship. What Success Looks Like Successful interns leave having delivered a complete research project from hypothesis through to evaluation under realistic market conditions, built statistically rigorous models, and demonstrated curiosity, ownership and the ability to solve open-ended problems. Who We're Looking For We're looking for exceptional researchers who genuinely enjoy solving hard problems. Full-time PhD student in a quantitative discipline such as mathematics, physics, computer science, statistics or a related field, graduating 2028 Strong programming skills in Python and/or C++ Depth in probability, statistics, linear algebra and optimization, with research experience in machine learning, statistical modelling or data analysis Comfort working with large, complex datasets, and strong analytical thinking A passion for applying quantitative thinking and rigorous research to solve open-ended problems in markets Strong communication skills, with the ability to explain complex ideas clearly Our Culture More than specific technologies, we care how you think. We look for people who are curious enough to question assumptions, analytical enough to separate signal from noise, persistent enough to keep searching past the first answer, humble enough to keep learning, and excited by problems without textbook solutions. At Graviton, researchers sit alongside engineers to solve problems where milliseconds matter and better models create real competitive advantage. You'll get meaningful ownership from day one, in a culture built on intellectual honesty and continuous improvement. Your contribution won't be measured by hours spent, but by the quality of your thinking. Markets are among the most complex systems humans have ever created. Every day, someone discovers a better answer. This summer, that someone could be you.
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