Lectureships/Readerships in Statistics and Data Science

The International Society for Bayesian Analysis
Edinburgh
2 months ago
Applications closed

Lectureships/Readerships in Statistics and Data Science

http://www.maths.ed.ac.uk/school-of-mathematics/jobs/lectureships-readerships-in-statistics-and-data-sc

Continuing an ambitious long-term plan, which includes expansion into part of the new £40M Bayes Centre, the School of Mathematics is making a number of permanent appointments in the Mathematical Sciences.

We are recruiting candidates with a track record of high quality research and teaching in Statistics and Data Science to start on 1 August 2018 or by agreement. The successful applicants will contribute to the growing reputation of the University as an international hub for Statistics and will join the recently established University-wide Centre for Statistics. They will interact with colleagues in the Bayes Centre, a new interdisciplinary Data Science Institute within the University, as well as the Maxwell Institute, a longstanding research partnership between the University of Edinburgh and Heriot-Watt University. They will also have opportunities to be actively involved with the Alan Turing Institute, a UK wide initiative in Data Science.

All applications must be submitted online and include a full CV, a research statement and a teaching statement. We also require details of four referees, three to comment on your research and one on your teaching.

Salary Scale: £39,992 – £47,722 per annum. Very strong and experienced applicants may be appointed to a Readership, for which the salary is £50,618 – £56,950 per annum.

Applications close at 5pm (UK time) on 3rd January 2018.

Informal enquiries may be made to Professor Ruth King (Thomas Bayes’ Chair of Statistics) .

The University of Edinburgh promotes equality and diversity. We strive for a family-friendly School of Mathematics; hold a Bronze Athena SWAN award and support the London Mathematical Society Good Practice Scheme.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Products

Where to Advertise AI Jobs in the UK (2026 Guide)

Advertising AI jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly informed and in demand across multiple sectors simultaneously. General job boards reach a broad audience but lack the specificity that AI professionals expect — and the filtering mechanisms they rely on. Specialist platforms, direct outreach and academic channels each serve a different part of the market. This guide, published by ArtificialIntelligenceJobs.co.uk, covers where to advertise AI roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about time-to-hire across different role types.

Jobs

New AI Employers to Watch in 2026: UK and Global Companies Reshaping AI Careers

The artificial intelligence job market in the UK is evolving at an extraordinary pace. With record-breaking investment, government backing, and a surge in enterprise adoption, the landscape of AI employers is shifting rapidly. For candidates exploring opportunities on ArtificialIntelligenceJobs.co.uk, understanding who is hiring next is just as important as understanding what skills are in demand. In this article, we explore the new and emerging AI employers to watch in 2026, focusing on organisations that have recently secured funding, won major contracts, or expanded their UK footprint. From cutting-edge startups to global giants doubling down on Britain, these companies represent the next wave of AI career opportunities.

Careers

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.