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    Lecturer (T&R) in Mathematics, Statistics and Data Science - 11382 - United Kingdom - Economicsnetwork

    Economicsnetwork
    Economicsnetwork United Kingdom

    3 weeks ago

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    Description

    Location: Brunel University London, Uxbridge Campus

    Brunel University London was established in 1966 and is a leading multidisciplinary research-intensive technology university delivering economic, social and cultural benefits. For more information please visit: .

    In the Department of Mathematics () we conduct research in a range of topics including applied analysis, computational mathematics, continuum mechanics, mathematical physics, financial mathematics, operational research, data science, and applied statistics, and we offer PhD supervision across all these areas. We run undergraduate courses in Mathematics, Mathematics with Computer Science, Financial Mathematics and Mathematics for Data Science, and postgraduate MSc courses in Financial Mathematics and Statistics with Data Analytics. We also offer an undergraduate course in Mathematics for Data Science delivered through a Transnational Education partnership with North China University of Technology (NCUT), Beijing, China. This is run by BUL faculty predominantly resident in China as well as flying faculty from BUL who spend a proportion of their time teaching at NCUT in a typical academic year.

    We are seeking to appoint a Lecturer in Mathematics, Statistics or Data Science/Analytics. The lecturer will be based at Brunel University London, UK, and will participate in the delivery of our UG programmes in the UK. As a part of their teaching duties, they may be called upon to contribute to the NCUT programme, by travelling to Beijing to teach on the Mathematics for Data Science BSc at NCUT and/or by providing online support for the NCUT provision.

    The role requires interaction and cooperation with academic colleagues in both BUL and NCUT in delivering teaching. The successful candidate will also be expected to join one of the Department of Mathematics' research groups (Applied and Numerical Analysis, Mathematical Physics and Applied Mathematics, Financial Mathematics and Operational Research, Statistics and Data Science) and to contribute to our thriving research environment.

    About you
    BUL delivers a variety of taught modules on its BSc programmes, encompassing applied mathematics, statistics, programming and data science. We welcome applications from candidates working in any areas of mathematics or statistics which add value to our teaching and contribute to one of our research groups. Applications from candidates with an ability and willingness to teach undergraduate and postgraduate modules in statistics, machine learning or data science and/or supervise final year projects in data science are particularly encouraged. It is expected that the applicants will have a significant research record as illustrated by refereed journal publications, commensurate with the level of appointment.

    For informal enquiries please contact either of the joint Heads of Department: or .

    We offer a generous annual leave package plus discretionary University closure days, excellent training and development opportunities as well as a great occupational pension scheme and a range of health-related support. The University is committed to a hybrid working approach.

    Closing date for applications: 3 June 2024.

    Interviews will take place online in June 2024.

    For further details about the post including the Job Description and Person Specification and to apply please visit .

    If you have any technical issues please contact us at: .

    All Applicants should be eligible to live and work in the UK for the duration of any offer of appointment.

    Brunel University London has a strong commitment to equality, diversity and inclusion. Our aim is to promote and achieve a fully inclusive workforce to reflect our community.

    £44,240 to £48,093 inclusive of London weighting with potential to progress to £56,903 per annum inclusive of London weighting through sustained exceptional contribution. Grade 8.

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