Open postdoc position on ‘Musical data science’ in ERC-funded project

DIDONE ( is an ERC-funded project jointly participated by the Instituto Complutense de Ciencias Musicales (ICCMU), the Universidad Complutense de Madrid (UCM), and the Universidad Carlos III de Madrid (UC3M). The project is led by Prof. Dr. Álvaro Torrente Sánchez-Guisande and involves 10 researchers, 4 music engravers, 3 correctors, and a project manager. Within DIDONE’s main aims are to (1) determine the compositional techniques whereby emotions were expressed in 18th-century opera seria, (2) develop a set of quantitative tools applicable to our and other repertoires, and (3) create a digital corpus of ca. 3,000 arias.

The postdoc researcher on ‘Musical data science’ is expected to engage and contribute in specific, varying-scale research problems within aims (1) and (2) in collaboration with DIDONE’s research team. S/he will work in tight collaboration with our music theorist, our senior statistician, and our software developer. S/he will be expected to focus on producing high-impact scientific literature at the interface between data/computer science and musicology, and on improving existent computational tools within the project that involve MusicXML and Python.

We offer:

– 1.5-year contract, with expected start date in April 2023 or earlier.
– Gross annual salary within the range €25,000–€32,000, depending on experience.
– Possibility of one-year contract extension.
– Possibility of salary increase upon the applicant’s acquisition of funding in immediate calls (*).
– An array of varying-scale research problems to be tackled.
– Working with a young, ambitious, and interdisciplinary research team with expertise in musicology, statistics, and computer science.
– Access to original curated datasets of ca. 1,000 newly digitised arias (in expansion).
– Possibility to co-supervise MSc theses in at least two master programs.

We look for a candidate with:

– PhD in Computer Science, Statistics, or similar.
– Strong publishing record in the above fields.
– Proven expertise in data analysis and statistical modelling or machine learning.
– Advanced musical knowledge.
– Experience in development with Python and using git.
– Knowledge on MusicXML or willingness to quickly obtain it.
– Ability to adapt and work in an interdisciplinary environment.

The work location is at UCM (Calle de Donoso Cortés, Madrid). The weekly dedication is 37.5h. The selected candidate will be hired by ICCMU and will be able to work in a hybrid format.

To apply for the position, send CV, list of publications, motivation letter, and at least one reference letter to before the application deadline on 15 February 2023. Address possible questions to that email address. The shortlisted candidates will be interviewed by videoconference in after 20 February 2023. Should more than one candidate be idoneous for the position, a pool of candidates will be created for future calls.

(*) These competitive calls include ‘Juan de la Cierva’ (deadline: 7 February) and ‘Ramón y Cajal’ (deadline: 9 February). Researchers interested in applying to these calls with DIDONE’s research group support must contact to express their interest at their earliest disposal.


The Didone Project has received funding from the European Research Council (ERC)
under the European Union’s Horizon 2020 research and innovation programme,
Grant agreement No. 788986.