Oferta de empleo: Científico de datos para trabajar en el proyecto Chordia

About the Instituto Complutense de Ciencias Musicales (ICCMU) The Instituto Complutense de Ciencias Musicales (ICCMU) is Spain’s leading academic centre dedicated to music. As part of the Universidad Complutense de Madrid, the ICCMU boasts over 30 years of experience in scientific research, the recovery and dissemination of musical heritage, and specialized music education. We are […]
ICCMU
17 de noviembre de 2025

About the Instituto Complutense de Ciencias Musicales (ICCMU)
The Instituto Complutense de Ciencias Musicales (ICCMU) is Spain’s leading academic centre dedicated to music. As part of the Universidad Complutense de Madrid, the ICCMU boasts over 30 years of experience in scientific research, the recovery and dissemination of musical heritage, and specialized music education. We are committed to promoting activities related to the creation, performance, and dissemination of music. The ICCMU is currently a partner in several major research projects, including two ERC Advanced Grants and the new synergistic project ChordIA-CM, funded by the Comunidad de Madrid.

About the ChordIA Project
The ChordIA-CM project: «Unveiling Musical Grammar», funded by the Comunidad de Madrid is a groundbreaking synergistic research initiative focused on studying the emergence and consolidation of the tonal system in Western music (1580-1750). This collaborative project brings together researchers from the ICCMU, the Universidad Nacional de Educación a Distancia (UNED-LENAR), and professionals from the Universidad Complutense de Madrid (UCM), under the leadership of Prof. Dr. Álvaro Torrente Sánchez-Guisande (ICCMU / UCM), and the Associate Professor Salvador Ros Muñoz (UNED).
ICCMU and the ChordIA project value diversity and are committed to creating an inclusive environment for all employees. We encourage applications from individuals of all backgrounds,  including but not limited to race, ethnicity, gender, sexual orientation, age, and disability.

Project AimsChordIA’s core objectives are
1. To create a large-scale, multimodal dataset of thousands of musical works (1580-1750), including digital scores (MusicXML, MIDI, MuseScore), harmonic annotations, text, and audio.
2. To develop an optimized sequencing format for training Large Language Models (LLMs) on symbolic music data.
3. To conduct a diachronic study of the relationship between poetic structure and harmonic planning using NLP techniques.
4. To design an agent-based architecture and multimodal models for the advanced analysis of harmony.
5. To establish a comprehensive evaluation framework and leaderboard for musical language models.

JOB OFFER

The Role: Data Scientist

We are seeking a highly motivated and talented Data Scientist to join our team and contribute to all five project objectives, with a special focus on objectives 1, 2, 4, and 5. As a key member of the ChordIA project, you will::

  • Engage in high-impact research at the intersection of AI, music informatics, and musicology, producing publications in top-tier journals and conferences.
  • Work closely with ChordIA’s musicologists, harmonic analysts, and the NLP/AI team at UNED.
  • Work with diverse musical formats (MusicXML, MuseScore, MIDI) from internal and external sources, ensuring the quality, interoperability, and integrity of the project’s corpus.
  • Contribute to the development, training, and evaluation of AI applications, including multimodal models and agent architectures for musical analysis.

Candidate Profile

  • Master’s degree (or equivalent) in Computer Science, Data Science, Music Informatics, or a related field.
  • Strong publication record in reputable journals or conferences, or equivalent research experience.
  • Proven expertise in data analysis, statistical modelling, and/or machine learning.
  • Advanced musical knowledge (e.g., music theory, harmony) is essential.
  • Expertise in software development with Python.
  • Demonstrable experience handling symbolic music formats, especially MusicXML and MIDI.
  • Excellent communication and collaboration skills.
  • Ability to thrive in an interdisciplinary research environment.

Desirable
A PhD in one of the fields listed above.
Experience with Large Language Models (LLMs) or Natural Language Processing (NLP).

We Offer

  • A full-time, 1-year contract, renewable annually for the project’s 36-month duration.
  • Gross annual salary starting from € 36.344,52. The final salary is negotiable based on the candidate’s academic and professional background.
  • The salary will be paid in 12 monthly instalments with prorated bonus payments.
  • Dynamic Research Environment: Work with an ambitious, interdisciplinary team of experts in musicology, AI, and computer science.
  • Unique Dataset: Access to a new, curated dataset of thousands of annotated scores from the 16th to 18th centuries .
  • PhD Opportunity: For candidates with a Master’s degree, we offer the possibility of developing a doctoral thesis based on the project’s research.
  • Pioneering Project: A key role in a groundbreaking research project at the intersection of AI and digital musicology.
  • Mentorship Opportunities: The opportunity to co-supervise MSc theses in relevant master’s programs (depending on the candidate’s experience).

Job Details
• Start Date: January 12, 2026
• Working Hours: Full time (37.5 hours per week).
• Work Arrangement: A combination of in-person and remote work is possible.
• Location: UCM, Calle de Donoso Cortés 63, Madrid, Spain.

Application Process
Submission: Interested candidates should submit a CV, a list of publications, a motivation letter (outlining research interests and relevant experience), and at least one professional reference letter to: chordia@iccmu.es.
Deadline: For priority consideration, please apply by Sunday, November 30, 2025 (23:59 CET). Applications will continue to be accepted on a rolling basis until the vacancy is filled.
Interviews: December 1-5, 2025


Proyecto ChordIA: Unveiling Musical Grammar, ref. SYG-2024/PH-HUM-801, financiado por la Comunidad de Madrid con las ayudas a Proyectos Sinérgicos de I+D 2024