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Artificial Intelligence and Music Technology● OpenPostdoc⏰ 6 days leftPreview

Research Associate in Music and Artificial Intelligence

Explore the intersection of music and AI to advance creative agency, artificial creativity, and health applications.

Best for:Best for AI researchers with a PhD in machine learning, computer science, or a related field, who are passionate about interdisciplinary collaboration and creative applications of AI in music and health.

University of Cambridge · Cambridge, United Kingdom · R2 · Recognised researcher
More professors at University of Cambridge
Generative AI in music creativityArtificial creativity and human-like unpredictabilityMusic AI for health and wellbeingEmpowerment vs. automation in creative processes
This is a postdoc position — not a PhD studentship.
Deadline
Oct 21, 2026
6 days
Funding
Salaried
£37.7k–£46.0k/yr
Start date
2027-01-01 or as soon as possible thereafter
Full-time
Location
Cambridge
United Kingdom

Overview

The University of Cambridge’s Faculty of Music seeks a Research Associate to investigate how AI can empower musicians, foster true creativity, and enhance health and wellbeing through music. Based in the Centre for Music and Science, the role involves leading a multi-year research project, collaborating with interdisciplinary teams including the Centre for Human-Inspired Artificial Intelligence and the Leverhulme Centre for the Future of Intelligence. The successful candidate will develop machine-learning systems, publish research, and contribute to teaching at both undergraduate and postgraduate levels. This fixed-term position offers a unique opportunity to bridge computational science and creative arts in a world-leading research environment.

Music AIGenerative AICreative AIMachine LearningHealth and wellbeing applicationsInterdisciplinary researchComputational musicologyAI creativity

What you'll do

  • Develop and evaluate machine-learning systems for music-related applications, focusing on one or more of the proposed research topics (e.g., enhancing musical creativity, fostering artificial creativity, or improving health and wellbeing through music).
  • Conduct independent research and publish findings in high-quality academic journals and conferences.
  • Collaborate with colleagues in the Centre for Music and Science, CHIA, and the Department of Computer Science to advance interdisciplinary research.
  • Deliver teaching at undergraduate and postgraduate levels, contributing to curriculum development and student mentorship.
  • Engage with the broader research community by participating in workshops, conferences, and public outreach initiatives.
  • Utilize state-of-the-art facilities, including professional concert halls, music libraries, and specialized research studios.

Requirements

Degree required: PhD in machine learning, computer science, or a related discipline

Language: English; proficiency appropriate for academic research and teaching

Instruction: English

Publications: Record of, or clear potential for, outstanding research output

Required skills
  • Proven expertise in developing, adapting, or evaluating machine-learning systems, particularly in creative or music-related domains.
  • Strong computational skills and experience with AI/ML methodologies.
  • Record of, or clear potential for, outstanding research output.
  • Ability to work collaboratively across disciplines, including music, cognitive science, and computer science.
  • Experience in interdisciplinary research environments.
Nice to have
Prior experience in music technology, computational musicology, or related fields.Familiarity with generative AI models and their applications in creative domains.Experience in teaching or mentoring students at the undergraduate or postgraduate level.
Eligibility
  • Open to all eligible candidates; no specific nationality or residency restrictions mentioned.

Funding & terms

Type
Salaried
Amount
£37.7k–£46.0k/yr
Duration
5 years (fixed-term)
Programme
University of Cambridge
University of Cambridge

How to apply

Deadline: 2026-10-21 (Europe/London)

Applicants must register an account with the University of Cambridge’s recruitment system and submit their application online. Required documents include a CV, cover letter, and research statement. Further details on application requirements are available in the provided advertisement.

Documents required
  • CV
  • Cover letter
  • Research statement
↗Apply on site

Contact

David Trippett· Professor

chair@mus.cam.ac.uk

DT
Prof.
David Trippett
Faculty of Music
Lab
Centre for Music and Science
University of Cambridge
United Kingdom
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