PhD Openings

Three fully-funded PhD openings at the DCML

The Digital and Cognitive Musicology Laboratory (DCML) at EPFL is recruiting three new PhD candidates to join the lab. The research focus of the lab lies in understanding music at the intersection between music theory, cognition and computation. Our research is at the forefront of scientific music research. We are looking for candidates in three different research areas:

  1. One PhD position in computational modeling of musical structure. The project seeks to model musical structure at the note level combining methodologies from music theory, reinforcement learning, Bayesian modeling, or deep neural networks.
  2. One PhD position in computational large-scale corpus modeling of the overarching historical development of musical structure over three centuries, at the intersection of musicology, music theory and digital humanities.
  3. One PhD position (open call) in music psychology and cognition, computational modeling of music, formal music theory, or computational musical creativity.

At DCML, you will join a growing interdisciplinary team of eight people with backgrounds from musicology, computer science and machine learning, psychology, cognitive science, and mathematics.

Your profile:

  • Applicants should have a Master degree in (empirical) musicology, computer science, psychology, cognitive science, music theory, mathematics, or a related field.
  • Skills in computer programming and statistics or data science; further experience in data science, machine learning or mathematical modeling is desirable.
  • Background or strong interest in (practical) music; knowledge of music theory and analysis is desirable.
  • Specific skills, depending on the applicant’s background:
    For applicants with a computational background, knowledge in machine learning, Bayesian modeling or mathematical modeling is essential.
    For applicants with a Digital Humanities background, knowledge in computational modeling or data science as well as music history is essential.
    For applicants with a psychology background, practical knowledge in experimental design and conducting experimental research is essential; experience with EEG is desirable.
    For applicants with a musicology background, strong knowledge in music theory as well as formal languages, mathematics (mathematical music theory), computer science or cognitive science is essential.
  • Very good analytical skills; experience in planning and conducting empirical research projects is desirable.
  • Team spirit and the ability to work in interdisciplinary collaborations
  • Fluent English language skills.

Our projects are funded by the SNF under the grant #215701 as well as the dotation of the Latour chair in Digital Musicology.

We offer:

At EPFL, doctoral students are regular full-term employees. Doctoral studies commonly last 4 years, with a candidacy exam after the first year.  The doctoral training also involves the opportunity to gain teaching experience. The EPFL provides an international academic ecosystem, excellent and stimulating research, training and teaching environment as well as a dynamic and lively international campus with a vibrant student life and cultural events.

Start date:

  • January 2024, however the start date is flexible.

Term of employment:

Fixed-term (CDD)

Work rate:

100%

Duration:

1 year, renewed after candidacy exam for a total of 4 years.

Contact:

All applications should be submitted online via the doctoral school of Digital Humanities (EDDH). (https://www.epfl.ch/education/phd/eddh-digital-humanities/). The application should specifically include a full CV and a cover letter (directed to Prof. Dr. Martin Rohrmeier), as well as three academic references. Details about the required application files are found at the submission portal. We strongly encourage female scholars to apply. For candidates with equal qualifications, preference will be given to people with disabilities.

Questions could be sent to [email protected]. Please do not submit your application via email.

Deadline for application:

The deadline is September 15, 2023.