Lecturer in Quantitative Methods

The London Interdisciplinary School (LIS) is a new university that equips students with an interdisciplinary toolkit to tackle the complex, real-world problems of the 21st century. With a world-class faculty, three exceptional founding cohorts, and close partnerships with global organisations, LIS is building a new type of education for those who want to shape the world, not just fit in it.

We are the first new UK education institution for 50 years to have full degree-awarding power from inception, and offer undergraduate and postgraduate degrees, as well as professional development programmes, that take an innovative approach to education.

We are now in our fifth year since the launch of our BASc in 2021. The first cohort of MASc students graduated in 2023. This year saw the launch of our MBA programme. The successful applicant for this post would therefore be joining us at an exciting time of development, growth, and consolidation.

About the Role: Assistant Professor in Quantitative methods (open specialism)

We are looking for a versatile and creative quantitative scholar to join our interdisciplinary faculty. At LIS, we believe quantitative methods should not be taught in isolation. Instead, they should be used as part of a rigorous toolkit to help understand and tackle the complexity of the 21st century.

Our foundational approach is rooted in computational and inferential thinking, using programming (in Python) as the primary engine for data analysis and inference. We are eager to expand our expertise. We are looking for a specialist who can bring a unique quantitative perspective to our students and the wider institution. You might have a background in:

• Physical Sciences: Applying concepts like modelling, entropy, dynamics, or scaling laws to social and environmental systems with a view to capturing common dynamics.
• Mathematics & Statistics: Teaching probabilistic reasoning and mathematical modelling as tools for thinking that can be applied both formally and heuristically across the disciplines.
• Network Science: Unpicking the hidden structures and connections that allow us to see physical, social, and cultural systems through the same lens.
• Game Theory & Decision Science: Analysing how strategic intelligence can be optimally deployed in complex environments and extracting non-obvious interdisciplinary insights from doing so.
• Data Science & AI: Exploring how the AI-driven explosion in cognitive resources can be deployed by students, teachers, and researchers in ways that push the frontiers of knowledge and practical utility.
• Alternatively, you might have experience of applying quantitative methods in government or industry.

Requirements

You should be:

• Experienced in teaching quantitative methods to students (at any level) and/or in applying quantitative methods in research projects.
• Fluent in a common programming language, preferably Python and/or R, and able to demonstrate substantial experience using these tools in teaching and/or research.
• Excited to work across diverse teams and help colleagues with non-quantitative backgrounds integrate these methods into their own teaching; conversely, you should be open to the insights of non-quantitative disciplines in yours.
• Interested in innovating your teaching methods to reach new students, with clear ideas about how to build a student's foundational understanding.

You should have:

• A PhD in a relevant quantitative field (e.g. Physics, Maths, Data Science, Statistics, Economics) or A PhD in a traditionally non-quantitative field in which you applied advanced quantitative methods; We also value equivalent high-level expertise from industry or government.
• A desire to break out of academic silos and apply your specialist knowledge to "wicked" problems like climate change, inequality, or global health.
• Experience with standard collaborative tools such as version control (e.g. Git), code review, and automated testing.
• An awareness of different approaches to interdisciplinarity, teaching styles, and inclusive pedagogy.
• A collaborative and adaptive mindset, such that you would thrive in a dynamic, academic environment.

What we offer:

• Permanent contract subject to completing probationary period;
• Salary for Lecturer is up to £45,000 depending on experience;
• 20% time dedicated to research;
• 30 days annual leave;
• Monthly fitness contribution;
• On successful completion of your probationary period, a company-sponsored private health plan;
• Annual learning budget to spend on professional development;
• The opportunity to join a mission-led, fast-growing organisation that is changing higher education.

Additional Information:

The role is available to start ahead of the 2026 academic year (on 21 September 2026), with a soft onboarding process during the summer to ensure readiness for start of the term.

Please submit your CV and a cover letter as part of your application (via the ‘Apply’ button above). The letter should include details of your teaching experience and philosophy, as well as why LIS would be a good fit. The letter of up to 2 pages should also include an example of a short course or module you would like to develop at LIS. You should explain how the course or module would fit into our current curriculum, as well as how you would ensure effective teaching for all students including those who ordinarily would not have studied quantitative subjects. You can consider undergraduate and/or postgraduate teaching.

Initially successful candidates will be asked to submit a video presentation. The next stage will consist of Panel Interviews and a mock teaching session.

Closing date: 15th July 2026 23:59 UK time