Open Positions


Full-time PhD position in music cognition at École Polytechnique Fédérale de Lausanne, Switzerland

The Digital and Cognitive Musicology Laboratory (DCML) at EPFL invites applications for a full-time PhD position in music cognition. The research project explores theories of musical syntax and structure and combines theoretical, computational and psychological approaches. We are looking for a candidate who shares the fascination for the musical mind and will join the team to work on psychological experiments exploring the perception and acquisition of syntactic structures in music. The research will be conducted in close collaboration with other project members working on theoretical and computational aspects of musical syntax. This PhD position is available in the context of the H2020-ERC funded project on the “Principles of Musical Structure Building: Theory, Computation, and Cognition”.

Required profile:

  • Applicants should have a very good MA degree in the fields of psychology, neuroscience, (empirical) musicology, cognitive science or a related field.
  • Skills in statistics, music theory and analysis as well as computer programming are desirable
  • Fluent English (French an asset)
  • Interest in working in a multidisciplinary, international environment

What we offer:

  • A young and dynamic lab with members from diverse disciplinary backgrounds (musicology, computer science, psychology, mathematics)
  • The EPFL provides an excellent and stimulating research and teaching environment as well as a dynamic and lively international campus with a vibrant student life and cultural events
  • Being located at the Lac Leman, Lausanne is a picturesque city with various possibilities for recreational and cultural activities

Start date and duration: The position is planned to start in early 2019 and last for 4 years. Term of employment: Fixed-term (CDD) at 100% work rate. The EPFL offers a competitive PhD salary.

Contact: PhD students upload their materials on under the EDNE doctoral school ( Female candidates are particularly encouraged to apply. For more information about the position, please contact Martin Rohrmeier (

Deadline for application: November 15, 2018

Internship positions

We are offering a paid internship (ca. PhD level) from October to December 2018 for someone with a background in computational or psychological research on music. If you are interested, please inform us by Monday, 6th August ( Feel free to get in touch if you have any questions.

Open Student Assistant positions

We are always looking for student assistants to collaborate with us.


  • interactive/live visualization and sonification of notes/music in the browser
  • interactive/live visualization of trees and graphs in the browser
  • interactive/live visualization of various patterns and structures relevant to music in the browser

Extending our music processing library 

We are in the process of building up an extensive music processing library by integrating existing frameworks as well as developing new functionality. Apart from basic audio processing functionality the library’s focus is on audio-to-symbolic transcription of music and music processing and analysis on the symbolic level. This includes things like

  • beat inference
  • measure inference
  • harmonic inference
  • motive analysis
  • integrating or reproducing the state-of-the-art, among others
  • reading/writing/converting between various commonly used formats
  • “rapid prototyping” (integration with visualization and sonification functionality from above)

Integration of music equipment 

  • We have different music equipment that has to be integrated with our music processing library. Among others our large digital/acoustic piano, a set of ROLI Lightpads, and a ROLI Seaboard.

Setting up a live framework 

  • There is a number of different tools that can be used for live music performances from acoustic and digital instruments to live-coding environments (sonic pi/super colider/common music/…) to algorithmic tools and autonomous artificial “musicians”. We need to set up a framework that integrates all these tools such that they can interact with each other and share a common “musical space”.

Developing an interface to create Schenker-graphs 

  • There are different options to realize this (from a LaTeX package or a browser-based solution to a Musescore plug-in) and part of the project is to explore these alternatives and find out which one best suits our needs.

Redesigning our website

  • This will involve some creativity in coming up with good designs and incorporating input/suggestions from the group as well as the technical realization thereof.

Crawling/digitalizing/transcribing music data

  • crawling the web for music data (scores, midi files, …) from different genres (classical music, jazz, pop, rock, …)
  • digitalizing/transcribing existing data (scanning of scores, transcribing scores by typing them into Musescore)

Conducting behavioural experiments

  • We have a number of behavioural experiment readily designed that need to be carried out. That is, participants need to be recruited, brought to the lab, and the data has to be recorded.

Neural Networks

  • learning voice-leading rules using feed-forward networks (simple) or recurrent neural networks (more advanced)
  • modelling the evolution of language and music via communication using autoencoders

Postdoc position (100%) at the Digital and Cognitive Musicology Lab, EPFL Lausanne

The newly established Digital and Cognitive Musicology Laboratory (DCML) at EPFL in Lausanne is recruiting a postdoc candidate to join the lab in the context of the H2020-ERC funded project on the “Principles of Musical Structure Building: Theory, Computation, and Cognition”. The research will focus on the theoretical and computational modelling of musical structure and syntax and computational corpus research.

Required profile

  • Applicants should have a PhD in the fields of (empirical) musicology, computer science, cognitive science or a closely related field.
  • High knowledge in computer programming, machine learning, statistical and mathematical modelling
  • Very good analytical skills; background or strong interest in music theory and analysis; experience in planning and conducting empirical research projects
  • Team spirit with the ability to work in interdisciplinary collaborations
  • Fluent English (French an asset)

What we offer

  • A young, dynamic and interdisciplinary team
  • Collaboration with strategic external partners and with advanced scientists
  • Term of employment: fixed-term (CDD)

Start date
Starting dates are flexible. We seek to fill the position as soon as possible.

Term of employment: Fixed-term (CDD)

Work rate: 100%

Duration: 1 year, renewable up to 3 years

Applicants should submit a cover letter, CV, list of publications and a list of two references with full contact information to Women are strongly encouraged to apply.

Deadline for application: Review of applications will continue until the positions are filled.