Lecturer (Teaching) in Financial Mathematics in London

Lecturer (Teaching) in Financial Mathematics in London

London Full-Time 81963 - 100177 £ / year (est.) No working from home possible
University College London

At a Glance

  • Tasks: Teach and supervise MSc students in Financial Mathematics at a prestigious university.
  • Company: Join UCL's renowned Department of Mathematics with a vibrant academic community.
  • Benefits: Enjoy 41 days of holiday, competitive salary, and professional development opportunities.
  • Other info: We encourage applications from underrepresented groups to enhance diversity.
  • Why this job: Make a real impact in financial mathematics while working with leading academics.
  • Qualifications: PhD in financial mathematics or related field, teaching experience, and Python proficiency.

The predicted salary is between 81963 - 100177 £ per year.

The Department of Mathematics at UCL is an internationally renowned department within one of the world’s most prestigious universities. Since its beginning, mathematics at UCL has been enhanced by its many outstanding members of staff. The department today is home to around eighty-four academic staff, including thirty-nine full professors, and a number of honorary staff, supported by a professional services team of twenty-five. Its community also includes around thirty-six Postdoctoral Research Fellows, around ninety PhD students, and fifty-four MSc students.

The broad range of research interests is reflected in the wide choice of courses available in the third and fourth years of the degree programmes, from spectral theory, groups and geometry to fluid mechanics and from mathematical ideas in biology to cosmology. Research funding in the department from EPSRC, ERC, NERC, Leverhulme Trust and the Wellcome Trust has grown significantly in recent years.

Applications are invited for a full-time Lecturer (Teaching) in Financial Mathematics position. This post is available from 28 September 2026 or as soon as possible thereafter until 31st July 2028.

An outstanding candidate will be a mathematician or quantitative researcher holding a PhD in financial mathematics, applied probability, numerical analysis, statistics or a closely related discipline, awarded or to be awarded before the start date. They will combine broad familiarity with core financial mathematics with command of the computational and numerical methods used in modern quantitative finance, and will be fluent in Python. They will also bring specialist expertise in an area of financial mathematics beyond the core syllabus, for delivery at Level 7 within an existing module. They will teach modules on the MSc Financial Mathematics programme in UCL's Department of Mathematics, as well as supervise MSc Financial Mathematics and other MSc students for their summer projects. Substantial experience of teaching quantitative subjects in higher education, strong communication, and a collaborative approach are essential.

We particularly welcome female applicants and those from an ethnic minority, as they are under-represented within UCL at this level.

As well as the exciting opportunities this role presents, we also offer some great benefits:

  • 41 Days holiday (27 days annual leave)

Lecturer (Teaching) in Financial Mathematics in London employer: University College London

University College London is an exceptional employer that fosters a vibrant and inclusive work culture, particularly within the Cultural and Community Engagement team at UCL East. As an apprentice, you will benefit from hands-on experience in communications while being supported by a team dedicated to your professional growth and development. With a focus on diversity and community involvement, this role offers unique opportunities to engage with various events and initiatives that make a meaningful impact.

University College London

Contact Details:

University College London Recruitment Team

We think you need these skills to ace Lecturer (Teaching) in Financial Mathematics in London

PhD in Financial Mathematics
Applied Probability
Numerical Analysis
Statistics
Core Financial Mathematics
Computational Methods
Numerical Methods