Senior Lecturer or Reader in Computational Statistics (Teaching & Research)

University of Manchester; Manchester; Hybrid; GBP 40,000 - 80,000; Full time

Job summary

An established industry player is seeking a talented academic to join their vibrant community in Manchester. This full-time position offers a unique opportunity to engage in cutting-edge research in Computational Statistics and Machine Learning while contributing to the education of future statisticians. The successful candidate will thrive in a supportive environment, teaching a range of courses and supervising students at both undergraduate and postgraduate levels. With a commitment to work-life balance and a range of family-friendly policies, this role promises not only professional growth but also personal fulfillment. If you're passionate about teaching and research, this opportunity is perfect for you.

Benefits

Market leading Pension scheme

Employee Assistance Programme

Exceptional annual leave entitlement

Paid closure over Christmas

Local and national discounts

Qualifications

• PhD in Statistics or a closely related field required.
• Outstanding research record in Computational Statistics is essential.

Responsibilities

• Conduct research in Statistics and supervise PhD students.
• Teach undergraduate and masters-level courses in Statistics.

Skills

Computational Statistics

Machine Learning

Data Science

Teaching Skills

Research Skills

Education

PhD in Statistics or related field

Job description

Applications are invited for the above post, to start in September 2025 or at a mutually agreed alternative date. We are looking for an academic of outstanding ability, who is seeking a friendly, supportive and collegial environment in which to develop as a world-class researcher and teacher.

Applicants should hold a PhD or equivalent in Statistics or a closely related field and be able to demonstrate an outstanding research record in an area of Computational Statistics as well as an ability to lecture a range of courses in Statistics and related areas at both undergraduate and postgraduate level.

The successful candidate will strengthen one or more of the following strategic research areas in the Department: biomedical data analysis, computational statistics and machine learning, foundations of data science and AI, high-dimensional data analysis, and uncertainty quantification.

We expect a genuine commitment to and enthusiasm for both teaching and research and the development of others. The successful candidate will carry out research in Statistics and supervise research (PhD) students. They will teach undergraduate and masters-level courses and contribute to the ongoing curriculum development. Furthermore, they will provide project supervision to students at undergraduate and masters-level in programmes offered by the Department. They will also perform other usual departmental duties, including examinations and further administrative tasks.

There are many opportunities to engage with other researchers at the University including the Institute for Data Science and Artificial Intelligence (https://www.idsai.manchester.ac.uk/). We are also a University Partner of the Alan Turing Institute (the UK national institute for data science).

The Department and University are committed to the well-being and work-life balance of all staff. We have a package of family-friendly policies covering flexible working, career breaks and entitlement to paid maternity, paternity and adoption leave. For more details on these and other benefits see https://www.manchester.ac.uk/connect/jobs/benefits-working-here/. The Department is fully committed to Athena SWAN principles to promote women in science and is a supporter of the LMS Good Practice Scheme; for more details of our activities relating to Social Responsibility see https://www.maths.manchester.ac.uk/connect/social-responsibility/. This is a full-time post but applications from individuals seeking part-time, job share or flexible working arrangements are welcome.

Candidates should provide a full academic CV, to which they should append:

1. a 2-page research statement outlining their research record and future plans;
2. a 2-page teaching statement outlining their teaching experience, approach and philosophy. This should also include descriptions of up to three dissertation projects (BSc, MSc) that could be offered to students;
3. a diversity statement (1-2 paragraphs) that describes their involvement with activities relating to equality, diversity, inclusivity and accessibility.

Please note that only one pdf file can be uploaded so please combine these documents into one file.

In addition, candidates should make sure to explain how they meet the essential and desirable criteria outlined in the person specification for the post. This information should be provided in the Supporting Information section of Jobtrain by listing each criterion as a paragraph heading and then explaining underneath how that criterion is met.

Proposed Interview Dates: 13th or 14th March 2025

What can you expect in return:

• Fantastic market leading Pension scheme
• Excellent employee health and wellbeing services including an Employee Assistance Programme
• Exceptional starting annual leave entitlement, plus bank holidays
• Additional paid closure over the Christmas period
• Local and national discounts at a range of major retailers

As an equal opportunities employer, we welcome applicants from all sections of the community regardless of age, sex, gender (or gender identity), ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.

Our University is positive about flexible working – you can find out more here. Hybrid working arrangements may be considered.

Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies. Any recruitment enquiries from recruitment agencies should be directed to [e-mail]. Any CVs submitted by a recruitment agency will be considered a gift.

Enquiries about the vacancy, shortlisting and interviews:

Name: Head of the Probability & Statistics Group within the Department of Mathematics, Professor Korbinian Strimmer

Email: [e-mail]

General enquiries:

Email: [e-mail]

Technical support:

https://jobseekersupport.jobtrain.co.uk/support/home

This vacancy will close for applications at midnight on the closing date.

Please see the link below for the Further Particulars document which contains the person specification criteria.