Assistant Professor in Statistics (Fixed term) (SCI165525)

This full-time fixed term position is available from 01 September 2025 [or as soon as possible thereafter] until 31st August 2028. Hours of work are full-time (36.25 hours); however applications are also welcome from candidates wishing to work part-time (minimum 29 hours per week) and job share arrangements may be considered. Many of our team have flexible working patterns so we're open to discussing flexible working arrangements with you. Requests for secondment from internal candidates may be considered on the basis that prior agreement has been sought from both your current line manager and the manager of your substantive post, if you are already undertaking a secondment role.

We are looking for proactive, organised appointees who can evidence:

• A PhD, or equivalent in Statistics or a related field.
• Good pedagogical skills to teach a range of statistics/probability (including service) modules.
• Proven track-record in publishing research work of international quality in statistics or related field.
• Excellent communication and organisational skills.
  
  We are looking for an Assistant Professor to deliver high quality teaching and undertake original research of international excellence in Statistics, complementing and enhancing the current activity of the Statistics and Probability (SP) Section. The School of Mathematical Sciences was ranked in the top 3 for quality of research environment and with 98% of our research being classed as 'world-leading' or 'internationally excellent'. The highly research active SP Section comprises 13 permanent academic staff with research interests in Bayesian computational statistics and machine learning, uncertainty quantification, Bayesian non-parametrics, image analysis, geometric statistics, and stochastic processes with an internationally leading research group in epidemic modelling. Furthermore, Section members collaborate with colleagues within the School and beyond, in projects at the interface of statistics, numerical analysis, scientific computation and the mathematics of machine learning.
We welcome applications from excellent candidates in any area of Statistics, but particularly welcome applications from those with an interest in machine learning or artificial intelligence. You will be able to carry out duties to the highest standard and to evidence how, through your experience, you will:
• Provide curriculum development within your own area of expertise and collaborate with colleagues to design and develop courses and/or programmes;
• Plan and deliver high quality teaching on undergraduate and postgraduate modules including via distance learning;
• Undertake original research and develop research proposals to attract funding from Research Councils and other sources;
• Contribute to the dissemination of research outputs at national/international conferences and workshops.