Lecturer (Teaching and Scholarship) in Music and Data Science

University of Leeds
Leeds
1 month ago
Applications closed

Related Jobs

View all jobs

Lecturer in Machine Learning for Engineering

Lecturer in Digital Innovation and Artificial Intelligence

Reader in Artificial Intelligence

Reader in Artificial Intelligence

Reader in Artificial Intelligence

Reader in Artificial Intelligence

Lecturer (Teaching and Scholarship) in Music and Data Science

University of Leeds


Are you an enthusiastic teacher, practitioner or researcher, committed to delivering a first-class learning and teaching experience with a demonstrated ability to teach effectively at undergraduate and postgraduate level? Are you passionate about delivering an exceptional student experience in a research-intensive Russell Group University?


The School of Music seeks to appoint a Lecturer in Music and Data Science to lead and develop our new Masters programme in this area, and to enhance educational provision focusing on data science applications in the music industry. You will offer demonstrable experience across both fields, whether acquired through industry experience, formal training, or active practice, and will bring together technical expertise, cutting‑edge understanding of contemporary applications of data science, and a genuine interest in music education. We particularly encourage applicants with combined experience in data science and digital marketing within the global music industry, whether in recording/streaming, music publishing or live music contexts.


Position Details

  • Mid/Senior level
  • Part‑time
  • Education and Training
  • Higher Education

Responsibilities

  • Teach undergraduate and postgraduate students in your specialist field using a diverse range of methodologies.
  • Carry out teaching, scholarship and management within the School.
  • Contribute to the supervision of student projects and the delivery of our curriculum beyond your specialist area.
  • Lead and develop our new Masters programme in Music and Data Science.

Qualifications

  • Postgraduate degree or relevant professional experience in music, data science, or related fields.
  • Demonstrated ability to teach effectively at undergraduate and postgraduate level.
  • Experience that combines technical expertise in data science with a genuine interest in music education.
  • Experience with data science and digital marketing in the global music industry is highly desirable.

Benefits

  • 26 days holiday plus approximately 16 Bank Holidays/University‑closed days – 42 days a year!
  • Generous pension scheme options plus life assurance.
  • Health and wellbeing: discounted staff membership to The Edge campus gym, pool, sauna, climbing wall, cycle circuit and sports halls.
  • Personal development: access to courses run by our Organisational Development & Professional Learning team.
  • On‑site childcare, shopping discounts and travel schemes.

Contact

Professor Bryan White, Head of School
Email:


#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.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.