Lullabyte. Unravelling the Effects of Music on Sleep through Musicology, Neuroscience, Psychology and Computer Science

Applications are invited for 10 PhD positions (Doctoral Candidates) to be funded by the Marie Skłodowska-Curie Action (MSCA) – Doctoral Network “Lullabyte” within the Horizon Europe Programme of the European Commission.

The Lullabyte network will train a group of 10 interdisciplinary doctoral candidates (DCs) in the three fields of musicology, neuroscience/psychology, and computer science. The aim is to provide the DCs with strong and intersectoral applicable research skills in empirical research on the effects of music and sound on sleep. The network consists of 10 excellent institutions from different areas, carrying out a broad range of interlinked studies, and combining the expertise of music research, psychology and neuroscience of sleep, and computer and data science. This creates a strong interdisciplinary and international network of researchers and leading non-academic partners, providing basis for cutting-edge research and innovative training tailored to the special needs of this interdisciplinary field of music and sleep.

Music exerts strong effects on the human brain, as evidenced by both subjective emotional reactions and overt changes in neurophysiology: lullabies are known in all cultures and times as an effective sleep aid for children and adults. However, musicology focuses mostly on musical structures, cultural practice or historical contexts, without interaction with empirical neuroscience. The Lullabyte project will for the first time bring leading researchers from musicology, sleep research, neuroscience and computer science together to fill this gap. Within the project, ten Doctoral Candidates will be trained in a radically interdisciplinary research field, and acquire profound skills relevant for industry and the cultural sector. Leveraging state-of-the-art neuroscience laboratories, big sleep datasets gathered with wearable technology, and data science strategies, the Doctoral Candidates will investigate the effects of music on the brain’s transition from wakefulness to sleep, from neurophysiological details of auditory processing in the thalamico-cortical system over changes in sleep structure induced by different kinds of music, to psychological and musicological analyses. Moreover, machine learning and sound design strategies will help to algorithmically generate novel, neuroscience-deduced music with particularly strong somnogenic effects. Beyond hands-on training in these research projects (with multiple possible secondments between the ten consortium partners), Doctoral Candidates will receive complementary training in technology transfer, entrepreneurship, medical device regulation and public outreach, through the project’s summer schools and satellite events with active participation of trainers from innovative industry partners and artists. As a whole, Lullabyte will train a new generation of interdisciplinary researchers, and thus provide the fast-growing market of personalized, algorithmically generated music with both a firm scientific basis and the personnel to strengthen Europe’s position in such technologies.

10 doctoral researcher positions are currently available.

Please find below the general as well as the individual positions’ descriptions and requirements. For more information on the open positions, please contact the partners directly depending on the research interest.

Eligibility criteria for the programme (all applicants):

- Applicants must not already hold a doctoral degree at the date of recruitment.

- The successful applicant (Doctoral Candidate) must be enrolled in a doctoral programme leading to the award of a doctoral degree.

Other eligibility criteria may apply depending on the recruiting partner. Please check the descriptions of the fellow positions.

The DCs will receive a salary according to MCSA regulation (page 78ff), including a living allowance, a mobility allowance and a family allowance, if eligible. (Country correction coefficient – see page 109)

Application (all applicants):

Please submit following documents for application: motivation letter, scientific CV, copies of certificates and academic qualifications (if applicable with English translation), two signed letters of reference, a copy of your ID, proof of language skills (if applicable, please check the fellow positions’ descriptions).

Fellow 1: Identifying of musical features of sleep music

The PhD student will focus on (i) Examining music used and subjectively or measurably preferred for sleep/relaxation on musical characteristics in order to extract common musical features, (ii) relate the findings to the cultural context and personal taste in wake state.

Recruiting institution: Institut für Kunst- und Musikwissenschaft, TU Dresden (Germany).

This project includes secondments with Emilia Gomez (Universitat Pompeu Fabra Barcelona, Spain) for MIR approaches and Kira V. Jespersen (Aarhus University, Denmark) for the psychological and demographic aspects. (6 months each)

Requirements: Master degree (or equivalent) in musicology, music technology, computer music, music psychology or related fields with strong skills in music research (e.g. proven by master thesis). A basic knowledge in quantitative analysis is required. Proof of English proficiency, as communication and teaching language throughout Lullabyte is English (e.g., TOEFL or similar test, not for native speakers). Basic knowledge of German is helpful, yet not required.

Applicants must not have resided or carried out their main activity (work, studies etc.) in Germany for more than 12 months in the last 36 months before the date of recruitment.

Start date (planned): 1st April 2023

Application period ended

Contact: Miriam Akkermann

Institut für Kunst- und Musikwissenschaft

Fachbereich Musikwissenschaft

01062 Dresden

 

Fellow 2: Analysis pipelines for big sleep data

The PhD student will focus on (i) developing multimodal analysis strategies/pipelines for large datasets of neurophysiological sleep recordings, (ii) integration/fusion of neurophysiological data from different sensors with non-physiological data and annotations.

Recruiting institution: Donders Sleep & Memory Lab, Radboud University Medical Center, Nijmegen (The Netherlands).

This project includes secondments with Dirk Pflüger (University of Stuttgart, Germany) on machine learning and big data strategies and Thomas Andrillon (Paris Brain Institute, France) on neurophysiological analyses of sleep.

Requirements: Master degree (or equivalent) in computer science, data science, AI, biomedical engineering or related fields. Experience (and strong interest) in neuroscience or related fields is beneficial. Demonstration of English proficiency, as communication and teaching language throughout Lullabyte is English (e.g. paper/thesis written in English or TOEFL or similar test).

Applicants must not have resided or carried out their main activity (work, studies etc.) in the Netherlands for more than 12 months in the last 36 months before the date of recruitment.

Start date (planned): April-September 2023

Application period ended

For further information and application please visit http://dreslerlab.org/lullabyte

Contact: Martin Dresler

Donders Institute for Brain, Cognition and Behavior

Radboud University Medical Center

martin.dresler@donders.ru.nl

Fellow 3: Real-Time Data Analysis and Predictions: From EEG sleep data to personalized auditory stimuli

An overall aim of Lullabyte is to enable a real-time interlink of the analysis of EEG sleep data and the generation of auditory stimuli. The PhD student will focus on 1) the development of new algorithms (including machine learning) for the analysis of EEG sensor data and the generation of auditory stimuli that are suited for real-time use, and 2) their efficient implementation to close the loop to be able to personalize auditory feedback during sleep in real-time in home settings.

Recruiting institution: Institute for Parallel and Distributed Systems, University of Stuttgart (Germany).

This project includes secondments with Thomas Andrillion (Paris Brain Institute, France) for EEG data measurements and Kira V. Jesperson (Aarhus University, Denmark) for data acquisition and analysis.

Requirements: M.Sc. in Computer Science, Mathematics, Simulation Science, Data Science or related fields with strong musical skills, programming experience (preferably C++ and Python) and strong mathematical expertise. Experience in machine learning / artificial intelligence or parallel programming are an asset. Proof of English proficiency is required, as the communication and teaching language throughout Lullabyte is English (e.g. TOEFL or similar test, not for native speakers). Knowledge of German is welcome, but not required. Applicants must not have resided or carried out their main activity (work, studies etc.) in Germany for more than 12 months in the last 36 months before the date of recruitment.

Start date (planned): June

Application period extended to April 30

Contact: Dirk Pflüger

Institute for Parallel and Distributed Systems

Universitätsstr. 38

70569 Stuttgart, Germany

Fellow 4: Factors determining the choice and impact of sleep music

The PhD student will focus on (i) modelling the influence of demographic, musical and psychological factors on the choice of sleep music and (ii) test the impact of different types of music on sleep using neuroimaging and behavioural methods.

Recruiting institution: Center for Music in the Brain, Aarhus University (Denmark).

This project includes secondments with Emilia Gomez (Universitat Pompeu Fabra Barcelona, Spain) for MIR approaches and Dirk Pflüger (University of Stuttgart, Germany) for machine learning approaches.Requirements: MSc in Cognitive Science, Neuroscience, Psychology, Medicine; M.A. in Music Psychology. Proof of English proficiency as communication and teaching language throughout Lullabyte is English (e.g. TOEFL, IELTS or Cambridge English Qualifications, not for native speakers). A project proposal must be part of the application. For details om the required documents for the application, please see: https://phd.health.au.dk/application/opencalls/predefined-phd-projects/application-guide-predefined-phd-projects. Applicants must not have resided or carried out their main activity (work, studies etc.) in Denmark for more than 12 months in the last 36 months before the date of recruitment.

Start data (preferred): 1st April 2023

Application period ended

Contact: Kira Vibe Jespersen

Center for Music in the Brain

Aarhus University

Universitetsbyen 3, building 1710

8000 Aarhus, Denmark

Fellow 5: Effects of acoustic stimulation of the sleeping brain: optimisation of musical features and subjective measures

Sleepers are not fully isolated from their environment as the brain continues to process external events to a surprising high level of complexity. This covert auditory processing can be leverage to the benefit of sleepers (e.g. to boost sleep slow waves, to help the consolidation of past memories or form new ones). However, any acoustic stimulation during sleep therefore faces the challenge of carefully finetuning sound features to each individual: while too silent stimulation might be ineffective, too loud stimulation might wake up the sleeping subject. In this project, the PhD student will develop and validate strategies to optimise and personalise acoustic stimulation procedures during sleep, and further test them with objective (physiological EEG readout) and subjective (post-awakening report) measures.

Recruiting institution: Paris Brain Institute, Paris (France).

This project includes secondments with Sergi Jorda (Department of Information and Communication Technologies, Universitat Pompeu Fabra Barcelona, Spain) and Martin Dresler (Donders Sleep & Memory Lab, Radboud university medical center, Nijmegen, The Netherlands).

Requirements: M.Sc. in Neuroscience, Cognitive Science, Biomedical Engineering, Psychology, or Computer Science; experience in computer programming (ideally Matlab or Python); experience in statistics and data processing; proof of English proficiency (e.g. TOEFL or similar test, not for native speakers). Desirable, but not required, are: experience with human-subject experimentation, and electrophysiological recordings in healthy individuals and/or patients.

Applicants must not have resided or carried out their main activity (work, studies etc.) in France for more than 12 months in the last 36 months before the date of recruitment.

Start date (planned): May-September 2023

Application period ended

For further information and application please visit https://thomas-andrillon.wixsite.com/research/join-us

Contact: Thomas Andrillon

INSERM & Paris Brain Institute
Hôpital de la Pitié-Salpêtrière

47 Bd de l'Hôpital,

75013 Paris, France

Thomas.andrillon@icm-institute.org

Fellow 6: Cracking the code of covert auditory perception during sleep using data-driven methods

Almost nothing is known about what types of sound are favored for transmission to the cortex during sleep, and current research exploring the optimal acoustic characteristics of, e.g., fire alarms do so with highly inefficient experimental paradigms (testing 2-3 sounds per night, waking up participants many times), which strongly limit scientific progress. In this project, the PhD fellow will investigate the use of modern data-driven techniques inspired by control engineering (such as reverse-correlation, temporal response functions and feedback system control) to analyse participants’ covert sensory electrophysiological responses to continuous streams of sounds, without interrupting their sleep.

Recruiting institution: Centre National de la Recherche Scientifique (CNRS), FEMTO-ST Institute, Besançon (France).

This project includes secondments with Björn Rasch (Université de Fribourg, Switzerland) for the recording of sleep EEG and Tarek Sharshar (GHU Paris Psychiatry & Neurosciences, Paris, France), for clinical applications to patients with disorders of consciousness (coma).

Requirements: The ideal applicant for this position holds a Master of Science with a background either in computational modeling (e.g., control engineering, physiological system modeling, computer science) with an interest in neuroscience, or in experimental psychology/neuroscience with an interest in computational methods (e.g., computational neuroscience, psychophysical data modeling). The position would be also suitable for a M.D. in Neurology/Sleep Medicine, with an appetite for computational methods. The project offers the best training potential for applicants who already have experience analysing awake/sleep EEG data, and have a solid programming background in Python, R or Matlab. Applicants must not have resided or carried out their main activity (work, studies etc.) in France for more than 12 months in the last 36 months before the date of recruitment.

Start date: 1st September 2023

Application period ended

For further information and application procedure, please visit https://neuro-team-femto.github.io/2022/11/09/LULLABYTE_PhD_position.html

Contact: Jean-Julien Aucouturier

FEMTO Neuro group, Dept. of Automation & Robotics, FEMTO-ST Institute

25000 Besançon, France

aucouturier@gmail.com (no application by email, see link above)

Fellow 7: Effects of interactive EEG based sonification and music generation, on sleep induction and sleep quality

The PhD student will (i) examine the potential effects of sonic stimulation on the electrical patterns of brainwave activity when sleeping and (ii) explore sonic biofeedback and interactive EEG based sonification, for facilitating relaxation, falling asleep, and for providing better sleep quality.

Recruiting institution: Music Technology Group, Department of Information and Communication Technologies (DTIC), Universitat Pompeu Fabra, Barcelona (Spain).

This project includes secondments with Thomas Andrillon (Paris Brain Institute, France) for EEG data measurements and neurophysiological analyses of sleep and with Sandra Pauletto (Royal Institute of Technology, Stockholm, Sweden) for sonification strategies.

Requirements: M.Sc. in Neuroscience, Cognitive Science, Biomedical Engineering, Psychology, or Computer Science; experience in electronic music production; experience in computer programming (ideally Python); experience in statistics and data processing; proof of English proficiency (e.g. TOEFL or similar test, not for native speakers). Desirable, but not required, are: experience with human-subject experimentation, machine learning, and audio programming (e.g. Pd, Max/MSP).

Applicants must not have resided or carried out their main activity (work, studies etc.) in Spain for more than 12 months in the last 36 months before the date of recruitment.

Start date (planned): 1st September 2023

Application deadline: 31st March 2023

For further information and application please visit https://www.upf.edu/web/mtg/ongoing-projects/-/asset_publisher/DneGVrJZ7tmE/content/id/262690045/maximized

Contact: Sergi Jordà

Music Technology Group, Department of Information and Communication Technologies (DTIC), Universitat Pompeu Fabra, Barcelona

Carrer Tànger 122-140 

08018 Barcelona

sergi.jorda@upf.edu

Fellow 8: Creative and analytical sonic interaction design and sonification of sleep data

The PhD student will focus on: 1) Identifying the acoustic features involved in promoting sleep, and whether they have a similar role in different sound signals (e.g. environmental sounds v.s. vocal sounds v.s. instrumental music); 2) Applying this knowledge to develop personalised interactive sonic applications that promote healthy sleeping behaviours (e.g. a real-time sonic feedback of sleep data; a personalised interactive sonic object that embodies and promotes a new and healthier relationship with one’s sleep behaviour)

Recruiting institution: Royal Institute of Technology (Sweden).

This project includes secondments with Miriam Akkermann (TU Dresden, Germany) to examine role of music and the singing voice in relation to sleep, and Thomas Andrillon (Brain Institute Paris, France) to deepen understanding of sleep data to be used for the development of personalised interactive sonic devices for sleep.

Requirements: M.Sc. in music technology, audio technology, sound computing, sound design, computer music, informatics with strong music and sound skills, media technology with strong music and sound skills, or equivalent. Proof of English proficiency - communication and teaching language throughout Lullabyte is English (e.g. TOEFL or equivalent test, not necessary for English native speakers).

Applicants must not have resided or carried out their main activity (work, studies etc.) in Sweden for more than 12 months in the last 36 months before the date of recruitment.

Start date (planned): June

Application period extended to May 5th

Contact: Sandra Pauletto

KTH (Royal Institute of Technology)

Lindstedtsvägen 3

114 28 Stockholm

Fellow 9: Testing algorithmic music with wearable EEG in home settings

The effectiveness of music for sleep has been evaluated mostly based on subjective impressions. Music, on the other side, has been not always developed in close relationship with these impressions. This applies mostly for lullabies only. We claim that we can enhance the effects of music on sleep quality when generating music that is especially designed and personalized for the sleepers needs. Thus, we generated first examples of algorithm-based music based on the subjective experiences in combination with theoretical considerations. However, an empirical test if and to what degree such music actually aids sleep still has to be performed.

This project aims at an empirical test of the effects of algorithmically generated music on sleep quality, using large-scale data acquisition using wearable EEG in home-settings.

Recruiting institution: Endel (Germany).

The project includes secondments with Martin Dresler (Donders Sleep & Memory Lab, Radboud university medical center, Nijmegen, The Netherlands) and Miriam Akkermann (TU Dresden, Germany) for 6 months each.

Requirements: Master degree (or equivalent) in musicology, music technology, computer music, music psychology or related fields with strong skills in music research (e.g. proven by master thesis). A basic knowledge in quantitative analysis is required. Proof of English proficiency, as communication and teaching language throughout Lullabyte is English (e.g., TOEFL or similar test, not for native speakers). Basic knowledge of German is helpful, yet not required.

Applicants must not have resided or carried out their main activity (work, studies etc.) in Germany for more than 12 months in the last 36 months before the date of recruitment.

Start date (planned): 1. April 2023

Application period ended

Contact: Katerina Flugelman Olmeda

Endel

Sophienstraße 21

10178 Berlin

Fellow 10: Sleep, Music and Emotional Processing

The PhD student will focus on (1) examining emotional reactions to musical stimuli presented during wakefulness and during sleep in healthy participants (2) examining effects of musical stimuli presented during sleep-on-sleep architecture and sleep quality in patients with insomnia. Emotional reactions will be measured using physiological recordings (EEG, EOG, EMG, SCR; HR, breathing).

Recruiting institution: University of Fribourg (Switzerland).

This project includes secondments with Jean-Julien Aucouturier (National Center for Scientific Research, France) to train in computational methods to design emotional musical stimuli and Kira V. Jespersen (Aarhus University, Denmark) for conducting studies on music and emotion in patients with insomnia.

Requirements: M.A. in Psychology, Cognitive Sciences, Cognitive Neurosciences or similar with strong musical skills. Proof of English proficiency, as communication and teaching language throughout Lullabyte is English (e.g. TOEFL or similar test, not for native speakers).

Basic knowledge of German and/or French is required. Applicants must not have resided or carried out their main activity (work, studies etc.) in Switzerland for more than 12 months in the last 36 months before the date of recruitment.

Start date (planned): 1st Mai 2023

Application period ended

Contact: Björn Rasch

Cognitive Biopsychology and Methods

University of Fribourg

Rue P.-A-de-Faucigny 2

CH-1701 Freiburg