New G-Research scholarships in machine learning

The University of Oxford’s Mathematical, Physical, and Life Sciences (MPLS) Division has announced a generous gift from G-Research, which will fund three DPhil scholarships within the department.

The three Graduate Scholarships, generously funded by G-Research, will focus on advancing research in machine learning. The scholarships are part of a package distributed across four departments: the Mathematical Institute (2 scholarships), Statistics (1 scholarship), Computer Science (3 scholarships), and Engineering Science (3 scholarships). The scholarships will roll out over three academic years.

This funding aims to support students with proven and potential academic excellence. By providing essential financial support, the scholarships will help unlock opportunities for talented individuals to make meaningful contributions to cutting-edge research in machine learning. In addition to financial support, students in receipt of these scholarships will benefit from a range of career development opportunities offered by G-Research, including:

• A bi-annual career mentorship meeting with a G-Research Quantitative Researcher
• A place on G-Research’s Spring into Quant Finance programme during the second year of the scholarship
• Invitations to presentations and seminars
• An annual dinner hosted by G-Research
• Brand ambassador status

Scholarships such as these are transformative, not only for the talented students who receive them but also for the academic communities they join. Thanks to the generosity of G-Research, these scholarships will enable some of the brightest minds to contribute to the advancement of machine learning, a field with the potential to revolutionise so many aspects of our lives. We are deeply grateful for this support. Professor Jim Naismith, Head of the MPLS Division

G-Research is a leading quantitative research and technology company, specialising in developing cutting-edge models and software for financial markets. Their commitment to advancing machine learning research and supporting future talent underscores their dedication to innovation and collaboration with the academic community.