At a Glance
- Tasks: Teach and research in statistics, focusing on AI and statistical computing.
- Company: Join the University of Edinburgh, a top global institution for mathematical sciences.
- Benefits: Competitive salary, generous leave, pension scheme, and flexible work options.
- Other info: Be part of a diverse community committed to equality and inclusion.
- Why this job: Shape the future of statistics and AI while inspiring the next generation of students.
- Qualifications: PhD in Statistics or related field with a strong teaching and research background.
The predicted salary is between 61759 - 61759 £ per year.
The University of Edinburgh is seeking to appoint a Lecturer in Statistics in the School of Mathematics. This is an exciting opportunity to join one of the world’s leading mathematical sciences departments and contribute to research and teaching. We are particularly interested in candidates with expertise in statistical computing and/or in the interaction between statistics and machine learning/artificial intelligence.
The appointment comes at an especially exciting time for the school, as we expand our activity in this area, including the planned launch of a new MSc in Statistics with Artificial Intelligence. We are therefore keen to appoint a colleague who can help shape this growing area in both research and postgraduate teaching.
The successful candidate will develop an independent and internationally recognised research programme in statistics, contribute to collaborative and interdisciplinary research, and support the school’s growing activities in AI-related statistical methodology and teaching. They will also contribute to undergraduate and postgraduate teaching across statistics, including course development, dissertation and project supervision.
The post sits within the School’s Statistics Group, part of the wider Data & Decisions Theme, which is active in modern mathematical and computational research in statistics, optimisation, and operational research. The Group has expertise in areas including spatial and spatio-temporal statistics, extremes, high-dimensional data, smooth regression modelling, causal inference, and the interface between statistics and machine learning/artificial intelligence. The School has strong interdisciplinary links across the University, including with colleagues in Informatics, Engineering, Geosciences, and the Institute of Genetics and Cancer.
Applicants should hold a PhD in Statistics or a related discipline, have a developing track record of internationally excellent research, and demonstrate a strong commitment to high-quality teaching at undergraduate and postgraduate level. We are looking for a colleague who will contribute fully to the academic life of the School and who shares our commitment to equality, diversity, and inclusion.
Further information about the School of Mathematics is available at www.maths.ed.ac.uk.
As a valued member of our team, you can expect:
- A competitive salary.
- An exciting, positive, creative, challenging and rewarding place to work.
- To be part of a diverse and vibrant international community.
- Comprehensive Staff Benefits, including generous annual leave entitlement, a defined benefits pension scheme, a wide range of staff discounts, family-friendly initiatives, and flexible work options.
Championing equality, diversity, and inclusion: The University of Edinburgh holds a Silver Athena SWAN award in recognition of our commitment to advance gender equality in higher education. We are members of the Race Equality Charter, and we are also Stonewall Scotland Diversity Champions, actively promoting LGBT equality.
Prior to any employment commencing with the University, you will be required to evidence your right to work in the UK. Further information is available on our right to work webpages.
The University is able to sponsor the employment of international workers in this role. If successful, an international applicant requiring sponsorship to work in the UK will need to satisfy the UK Home Office’s English Language requirements and apply for and secure a Skilled Worker Visa.
The closing date for applications is 10 July 2026. Unless stated otherwise the closing time for applications is 11:59pm UK time.
Lecturer in Statistics in Edinburgh employer: University of Edinburgh
The University of Edinburgh is an exceptional employer, offering a vibrant and inclusive work environment within one of the world's leading mathematical sciences departments. As a Lecturer in Statistics, you will benefit from a competitive salary, comprehensive staff benefits, and opportunities for professional growth through interdisciplinary collaboration and innovative research initiatives, particularly in the exciting field of statistics and artificial intelligence. Join a diverse international community committed to equality, diversity, and inclusion, where your contributions to teaching and research will be valued and supported.
StudySmarter Expert Advice🤫
We think this is how you could land Lecturer in Statistics in Edinburgh
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like University of Edinburgh!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Lecturer in Statistics at University of Edinburgh.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like University of Edinburgh.
✨Apply Directly through Our Website
When you find a suitable opening like Lecturer in Statistics at University of Edinburgh, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Lecturer in Statistics in Edinburgh
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at University of Edinburgh, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at University of Edinburgh. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at University of Edinburgh
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at University of Edinburgh!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
