Florence Nightingale Bicentenary Fellow and Tutor in Computational Statistics & Machine Learning, University of Oxford

Virksomhed

Oxford University

Ansøgningsfrist

November 28, 2022

The Department of Statistics is recruiting to two Florence Nightingale Bicentenary Fellow and Tutor in Computational Statistics & Machine Learning posts. These are career development positions intended to carry around half the teaching load of an ordinary Oxford faculty position. The successful candidates would be expected to take up their roles by 1 September 2023. Start-up funding of £3,000 will be available.

The post holders will join the dynamic and collaborative Department of Statistics. The Department carries out world-leading research in core theoretical statistics, computational statistics, machine learning and probability as well as applied statistics fields, including statistical and population genetics and bioinformatics.

The successful candidate will hold a relevant PhD/DPhil with post-qualification research experience in the area of computational statistics and machine learning. For Grade 7, the successful applicant is not required to have post-qualification research experience, but will hold or be close to completion of a relevant PhD/DPhil. They will have a strong publication record and sufficient specialist knowledge to develop research projects, along with effective teaching and supervision skills.

If you would like to discuss this post and find out more about joining the academic community in Oxford, please contact Professor Arnaud Doucet, arnaud.doucet@stats.ox.ac.uk, or Professor Judith Rousseau, judith.rousseau@stats.ox.ac.uk. All enquiries will be treated in strict confidence and will not form part of the selection decision.

This post is fixed-term for three years.

Only applications received before 12.00 midday on 28 November 2022 will be considered.

Please find the full advert at https://my.corehr.com/pls/uoxrecruit/erq_jobspec_version_4.display_form?p_company=10&p_internal_external=E&p_display_in_irish=N&p_process_type=&p_applicant_no=&p_form_profile_detail=&p_display_apply_ind=Y&p_refresh_search=Y&p_recruitment_id=161325