Lecturer in Quantitative Methods (Open Specialism)

About the role

The London Interdisciplinary School is seeking a versatile quantitative scholar to join its interdisciplinary faculty as a Lecturer in Quantitative Methods. You will help embed quantitative thinking across a range of programmes, using Python as the core engine for data analysis and inference.

Key responsibilities

• Design and deliver undergraduate and postgraduate modules that integrate computational, inferential, and statistical thinking.
• Develop teaching materials that link quantitative methods to physical sciences, mathematics, network science, game theory, decision science, and data‑science applications.
• Mentor students on interdisciplinary projects, guiding them to apply quantitative tools to social, environmental, and technological challenges.
• Collaborate with faculty to expand the school’s quantitative expertise and contribute to curriculum innovation.
• Engage with external partners in government or industry to bring real‑world quantitative case studies into the classroom.

Required profile

• Proven experience teaching quantitative methods at university level or in a comparable professional setting.
• Strong interdisciplinary background, e.g., physical sciences, mathematics & statistics, network science, game theory, decision science, or data science & AI.
• Ability to translate complex quantitative concepts into accessible learning experiences for students from diverse disciplines.
• Track record of research or applied work that demonstrates innovative use of quantitative techniques.
• Commitment to the school’s mission of interdisciplinary education and tackling 21st‑century challenges.

Required skills

• Python programming for data analysis and inference.