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Lecturer in Applied Mathematics (Optimisation)

King's College London

London
CDI
Temps plein
Mathematics & Statistics
Publié le 10 novembre 2026

Description du poste

About us: King’s College London is a world-leading university based in the heart of London. The Faculty of Natural, Mathematical & Engineering Sciences brings together research and education in mathematics, physics, chemistry, computer science and engineering, with a strong emphasis on interdisciplinary collaboration, innovation and addressing fundamental scientific questions and wider societal challenges. The Department of Mathematics, based at the University’s Strand Campus in central London, has a long and distinguished tradition in pure and applied mathematics, dating back to the appointment of King’s first Professor of Mathematics in 1830. About the role: Applications are invited for a Lectureship in Optimisation with a focus on continuous and stochastic optimisation (mathematical programming) in the Department of Mathematics at King’s College London. The appointment forms part of the continued strategic development of Mathematics at King’s and offers an exciting opportunity to contribute to research in optimisation and teaching in mathematics, in line with King's Strategy 2030. The postholder will develop an independent research programme in mathematical modelling and optimisation while creating opportunities for collaboration within the Department of Mathematics and more widely across King’s College. They will be expected to contribute to the research activities of one or more of the Department’s research groups and to enhance the research profile of the Department through publications, participation in scientific meetings, and collaboration with national and international partners. The role also involves undergraduate and postgraduate teaching and assessment, supervision of research students, and a contribution to the delivery of an excellent and inclusive student experience. The postholder will play a key role in developing the optimisation and modelling components of the new BSc in Quantitative Modelling, launching in September 2027, with a particular focus on applying optimisation techniques to real-world problems. In addition, the successful candidate will contribute to the wider intellectual and institutional life of the Department through scholarly engagement, collaboration with colleagues within and beyond King’s, and participation in the organisation and collegial structure of the Department. This is a full-time position (35 hours per week) and an indefinite contract will be offered. The position is based at the Strand Campus of King’s College London, with an expected start date no later than September 2027. About you: To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD in Mathematics, Applied Mathematics or in a closely related discipline with a strong mathematical component (e.g. operations research, mathematical programming, statistics). A strong research profile in continuous optimisation and its applications evidenced by publications in high-quality journals. Demonstrable potential to attract external research funding. A clearly articulated research vision that provides a compelling rationale for the proposed research activities and demonstrates excellent communication and interpersonal skills. Expertise in optimisation and computational approaches to quantitative problems Ability to teach undergraduate and postgraduate modules in mathematics and to supervise postgraduate research students. Ability to contribute effectively to academic administration and the wider collegial responsibilities of the Department. Excellent organisational, analytical and problem-solving skills and ability to use own initiative and think critically. Desirable criteria Experience working with industry or applied research environments in a role involving computational optimisation Experience developing or leading undergraduate modules. Experience integrating computational or modelling tools into teaching. Experience of project-based learning and assessment. Interviews are provisionally due to be held early February 2027.