Michael Nelson

Michael Nelson has a strong background in quantitative research and data analysis. Michael is currently working at Keyrock as the Head of High Liquidity Quantitative Research and also holds the role of Quantitative Researcher and Strategist. Prior to this, they were the Head of Quantitative Research at Voltz Labs, where they focused on fixed-income derivatives trading and modeling in decentralized finance. Michael also applied machine learning and data science to cryptocurrency markets and built quantitative strategies.

Before joining Voltz Labs, Michael worked as a Research Fellow at the University of Cambridge, specializing in machine learning, computational biology, biophysics, and data science. Michael used statistical and deep learning techniques to study genetic data and the development of cancer. Michael also conducted research on Bayesian inference to understand the clonal properties of cancer.

Michael also has experience as a Quantitative Researcher at Winton, where they applied machine learning and statistics to systematic futures trading strategies, FX macro quantitative strategies, and options hedging strategies. Additionally, they worked as a Postdoctoral Research Fellow at Stockholms universitet, where they performed complex data analysis and used machine learning techniques for searches in di-Higgs production at the Large Hadron Collider with the ATLAS experiment.

Earlier in their career, Michael was a PhD student at the University of Oxford, completing their doctoral research in physics. Michael also worked as a Graduate Teaching Assistant and Undergraduate Tutor at the University of Oxford, where they provided teaching and guidance to particle physics students. In addition, they had the opportunity to work at CERN as both a PhD student on a long-term attachment and as a summer intern. During their internship at DESY, they focused on hardware and alignment projects with the ATLAS experiment.

Overall, Michael Nelson's work experience showcases their expertise in quantitative research, data analysis, machine learning, and statistical techniques applied to various industries such as finance, biology, and physics.

Michael Nelson completed their education at the University of Oxford, where they obtained a Doctor of Philosophy (D.Phil.) degree in Particle Physics. Michael attended the university from 2015 to 2019. Before that, they studied at the University of Cambridge from 2011 to 2015, where they earned a Master of Arts (M.A.) and a Master of Natural Sciences (M.Sci.) degree in Experimental and Theoretical Physics.