Reader​/Professor in Mathematical or Statistical Data Science

Newcastle University is a great place to work, with excellent benefits. We have a generous holiday package, a number of health and wellbeing initiatives, plus the opportunity to buy more, great pension schemes, and a variety of supportive programmes.

Closing Date: 14 June 2026

Applications are invited at Reader or Professor level in Mathematical or Statistical Data Science, broadly interpreted to include AI. The role will be based within the Statistics and Data Science section in the School of Mathematics, Statistics & Physics (MSP), with a flexible start date to be agreed.

You will be expected to carry out excellent research and teaching in an area of Mathematical and/or Statistical Data Science which complements and strengthens existing activities within the School. In addition, there is an opportunity to engage with applied Data Science across a wide range of disciplines within the University, including the School of Computing and the Faculty of Medical Sciences.

You will contribute to the research profile of the Statistics and Data Science Section within MSP by publishing in internationally recognised journals, demonstrating research impact, and securing external research funding. Additionally, you will be a key contributor to the Data Science 2030 (DS2030) faculty project to broaden our institutional offering in data science and, alongside the related AI2030 project, artificial intelligence.

This will comprise a joined‑up educational offering at UG and PGT levels, and will be sector‑leading in providing forward‑facing data skills embedded in academic units across all parts of the university. DS2030 will act as a solid platform to build tangible cross‑institutional research and business engagement opportunities. DS2030 will be supported by strategic investment and the role holder will be a critical contributor to the success of the project.

• Provide academic leadership in Mathematical and/or Statistical Data Science, shaping research direction and contributing to the strategic development of the school.
• Lead and contribute to interdisciplinary research initiatives across statistics and data science and related fields. Publish refereed articles in venues of international standing appropriate to Data Science.
• Collaborate with colleagues in the Statistics and Data Science section, and with colleagues from other disciplines within the university on applied Data Science. Seek out funding opportunities and develop grant‑funded research projects.
• Attract, supervise, and mentor doctoral researchers and postdoctoral associates across a broad range of Data Science disciplines.
• Build and maintain strategic links with industry, government and external stakeholders in order to contribute to the development of applied, methodological or theoretical Data Science.
• Lead the design and delivery of research‑inspired teaching.
• Deliver high‑quality teaching and assessment at undergraduate and postgraduate levels, and contribute to programme development, accreditation and academic leadership in education.
• Carry out administrative duties as assigned by the Head of School and the School Executive Board.

• Excellent grasp of both the Mathematical and/or Statistical foundations of Data Science.
• An outstanding research profile commensurate with career stage, with a strong publication record in Mathematical and/or Statistical Data Science, evidenced by publications in leading venues and other esteem indicators appropriate to Data Science.
• A record of successful research income generation, either in own name or as a major contributor, with evidence of leading collaborative research success in statistics and data science.
• A strong track record of successful supervision of PhD students and postdoctoral researchers.
• Demonstrable ability to effectively teach at university level, including experience of programme development. Evidence of development of, and ability to deliver, innovative and effective teaching and learning materials across a broad range of statistics and data science modules with an ability to create ideas for course development at undergraduate and…