Lecturer in Statistical Learning

1 month ago

Southampton, United Kingdom University of Southampton Full time
2684824PJ

We are seeking an outstanding candidate for a lectureship in Statistical Learning, interpreted broadly, as part of an expansion in Artificial Intelligence and Data Science research and education in the School of Mathematical Sciences. This position arises thanks to a significant new investment by the University to support our ambitions to further develop our strengths in this important area.

Mathematical Sciences forms part of the Faculty of Social Sciences, which brings together a unique range of disciplines and is committed to tackling the world’s biggest challenges through interdisciplinary research. Academics from Mathematical Sciences are also members of the wider centres of Southampton Statistical Sciences Research Institute (S3RI), which coordinates statistical research across the University, and the Centre for Operational Research, Management Science and Information Systems (CORMSIS). In the latest (2023) QS World University Rankings, Statistics and Operational Research at Southampton was ranked 7th in the UK and 39th in the world.

The University of Southampton is part of the Alan Turing Institute for Data Science and Artificial Intelligence and has an ethos of promoting collaborative methodological research across disciplinary boundaries. This is exemplified by each of Mathematical Sciences, S3RI and CORMSIS, which bring together broad groups of mathematicians and statisticians who collaborate widely across the University and beyond. Mathematical Sciences has a varied set of external partners, including government agencies and departments, such as the Office for National Statistics, the Met Office, the pharmaceutical and other manufacturing industries, and UK public health bodies and the NHS. 

You will have a track record of excellent research in Statistics or an aligned discipline with an emphasis on statistical learning, ideally with interests that span across to other areas of Mathematical Sciences (principally mathematical modelling or operational research) and enhance or complement our existing strengths in statistical modelling and computation, uncertainty quantification, design of experiments, biostatistics, or financial and actuarial mathematics.

Strong applicants should demonstrate:

- A PhD or equivalent professional qualifications and experience in a relevant discipline

- Ability to obtain peer-reviewed funding 

- Evidence of distinction in research through high-quality publications 

- Ability for undergraduate and postgraduate teaching

The School of Mathematical Sciences offers a diverse and welcoming workplace at a world-leading University with a strong opportunity for engaging in multidisciplinary projects. We were very proud to have been awarded the Athena Swan Silver award, and we are committed to the Equality, Diversity, and Inclusion principles in all aspects of our work. We strongly encourage applications from women and other groups under-represented in Mathematics and Statistics. We encourage applications from those who have taken career breaks for reasons including maternity, paternity or adoption leave, disability, or illness. The University has a generous maternity policy and onsite childcare facilities and offers a range of benefits designed to help maintain and support employees' well-being and work-life balance. The University of Southampton is committed to sustainability and being a globally responsible university and has been awarded the Platinum EcoAward.

Discover how the University of Southampton is investing in its people and key impact themes, AI and Data Science, Sustainability and Resilience, Decarbonisation and Engineering Better Health and view all the exciting opportunities on offer by visiting our campaign site

Please upload a copy of your CV with your application.

Further details:

Job Description and Person Specification

We are committed to equality, diversity and inclusion and welcome applicants who support our mission of inclusivity.


lang: en_US

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