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2026 Research Internship
hace 2 semanas
Barcelona – 4 months – Paid Internship
Co-supervised by BMAT & MTG (UPF)
BMAT Music Innovators is a global music technology company dedicated to understanding, identifying, and organising all the music in the world.
Our R&D & Innovation department works on cutting-edge research in audio, metadata, AI models, and large-scale music data systems.
For 2026, we are opening 2 Research Internship positions for highly motivated students (preferably PhD candidates, though Master's students might be also considered) seeking an international research stay with real industry impact, academic guidance, and an opportunity to contribute to a future scientific publication.
Why this internship is uniqueHosted under the UPF-BMAT Chair on Artificial Intelligence and Music*, this project represents a unique blend of academia and industry led by leaders in their respective fields.
You will experience a rare hybrid ecosystem:
- MTG (Music Technology Group, UPF). Renowned academic research group in AI & Music.
- BMAT Music Innovators. Industry leader applying research at global scale.
You'll work on real-world music datasets, explore frontier research problems, and co-develop work aimed at scientific publication. You'll be integrated into both environments, gaining academic mentorship + industry exposure — something very few research internships in music tech can offer.
Research TopicsProjects can be adapted to your background and research interests. Possible areas include:
- Music Identification (Audio Fingerprinting and Version Identification)
- Music Metadata Processing with Natural Language Processing
- Explainable & Knowledge-based AI for Music Data
- Representation & Multimodal Learning
- Detection and Analysis of AI-generated Music
- Currently pursuing a PhD or a Master's degree.
- Background in: Computer Science, Machine Learning, Music Information Retrieval, Natural Language Processing, Engineering, Mathematics or related fields.
- Strong programming and machine learning skills
- Curiosity, critical thinking, and a strong sense of scientific rigor.
- Interest in contributing to a publication-oriented research project.
- Publications in relevant conferences or journals (ISMIR, ICASSP, ICML...)
- Co-design and carry out a research project with joint supervision from MTG and BMAT.
- Develop ML/NLP/MIR models and evaluate them on real-world music datasets.
- Contribute to research documentation and publication preparation.
- Participate in internal research meetings and discussions with industry teams.
We have 2 positions available. This posting will be removed once filled.
- Duration: 4 months (flexible start date; can occur any time during the year).
- Compensation: This is a paid internship.
- Mobility support: We offer financial support for relocation or travel, depending on the intern's needs.
- Barcelona HQ office available to you, kitted out with a rehearsal room
- We'll provide you with all equipment needed for you to be comfortable
- Contract issued by: MTG (UPF).
- Housing: Not provided.
- Application submission
- Screening based on research background
- Technical assignment
- Interview
- Deep review of your background
- Evaluation of critical thinking and methodological approach
Diverse perspectives drive innovation, and innovation is kind of our thing. Our open-minded and flexible culture organically fosters this diversity. We've learnt that we thrive on learning from each other, so we don't just welcome but actively hire a range of open-minded people from all walks of life. Our team is made up of people with different backgrounds, perspectives, orientations, abilities, musical tastes, dress sense and time-zones - but we all have one common goal: Making the music world a better place. With equal opportunities for everyone, BMAT is a pretty nice place to work.
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*Cátedra UPF-BMAT en Inteligencia Artificial y Música (TSI Project funded by Secretaría de Estado de Digitalización e Inteligencia Artificial, the European Union-Next Generation EU, and by BMAT Music Innovators, the Music Operating System
