Monday, December 9, 2019

Fwd: Special Collection on “Music and Autobiographical Memory”: Deadline Extended to April 30, 2020


Call for Submissions for Special Collection on "Music and Autobiographical Memory": Deadline Extended to April 30, 2020


Submissions for contributions to the Special Collection "Music and Autobiographical Memory," to be published in the journal Music & Science, are currently being accepted. The goal of this Special Collection is to highlight recent work related to the topic of music and lifetime memories. Potential topics include: Differences between music and other sensory cues for memory, music as a memory cue in neurological disorders, the neural substrates of music-evoked memories, music-evoked memories in everyday life, music-evoked memories across the lifespan, memories for musical events, music and the self, among other relevant topics. 


The deadline for submissions has now been extended to April 30, 2020. 


Please note that, as an open access journal, Music & Science will be introducing an Article Processing Charge (APC) from the start of 2020 ($400 USD + VAT per article, with a 50% discount for SEMPRE members). Therefore, any articles submitted after December 31, 2019 (the original submission deadline) will incur an APC if accepted for publication. Authors may, however, apply for an APC fee waiver upon submission; fee waivers are granted at the discretion of the editorial board.

 

Instructions for submission and further information can be found here: journals.sagepub.com/page/mns/special-collections/music-and-autobiographical-memory

 

Please contact the guest editors of this special collection if you have any questions:

Amy Belfi (amybelfi@mst.edu)

Kelly Jakubowski (kelly.jakubowski@durham.ac.uk)


Fwd: PhD studentships in Artificial Intelligence and Music (AIM) at Queen Mary University of London



UKRI Centre for Doctoral Training in Artificial Intelligence and Music (AIM), Queen Mary University of London
https://www.aim.qmul.ac.uk/

Up to 12 fully-funded PhD studentships to start September 2020
Covers fees and a stipend for four years
Application deadline: 31 January 2020

Why apply to the AIM Programme?
  • 4-year fully-funded PhD studentships available
  • Extensive choice of projects, drawing on a supervisory team of over 30 academics
  • Access to cutting-edge facilities and expertise in artificial intelligence (AI) and music/audio technology
  • Comprehensive technical training at the intersection of AI and music through a personalized programme
  • Partnerships with over 20 companies and cultural institutions in the music, audio and creative sectors
More information on the AIM Programme can be found at: https://www.aim.qmul.ac.uk/

Programme structure
Our Centre for Doctoral Training (CDT) offers a four year training programme where students will carry out a research project in the intersection of AI and music, supported by taught specialist modules, industrial placements, and skills training. Find out more about the programme structure at: http://www.aim.qmul.ac.uk/about/ 

Who can apply?
We are on the lookout for the best and brightest students interested in the intersection of music/audio technology and AI. Successful applicants will have the following profile:
  • Hold or be completing a Masters degree at distinction or first class level, or equivalent, in Computer Science, Electronic Engineering, Music/Audio Technology, Physics, Mathematics, or Psychology. In exceptional circumstances we accept applicants with a first class Bachelors degree who do not hold a Masters degree, provided that applicants can provide evidence of equivalent research experience, industry experience, or specialist training.
  • Programming skills are strongly desirable; however we do not consider this to be an essential criterion if candidates have complementary strengths.
  • Formal music training is desirable, but not a prerequisite.
For this round of applications we are offering a number of scholarships to applicants who are ordinarily resident in the UK (i.e. have lived and studied/worked in the UK at least the last three years - this includes EU nationals) and a smaller number of scholarships to international students.

Funding
We have a large number of 4-year PhD studentships available for students starting in September 2020 which will cover the cost of tuition fees and will provide an annual tax-free stipend  (£17,009 in 2019/20). The CDT will also provide funding for conference travel, equipment, and for attending other CDT-related events.

The AIM programme also welcomes applications from students who have sponsorship for PhD study from numerous international funding agencies and also accepts self-funded students. For more information on external PhD studentships and self-funded please visithttp://www.aim.qmul.ac.uk/apply .

Apply Now
Information on applications and PhD topics can be found at: http://www.aim.qmul.ac.uk/apply
Application deadline: 31 January 2020
Application deadline for China Scholarship Council applicants only: 12 January 2020
For further information on eligibility, funding and the application process please visit our website. Please email any questions to aim-enquiries@qmul.ac.uk 


— 
Dr. George Fazekas, 
Senior Lecturer in Digital Media 
Programme Coordinator, Sound and Music Computing (SMC)
Centre for Digital Music (C4DM)
School of Electronic Engineering and Computer Science
Queen Mary University of London, UK
FHEA, M. IEEE, ACM, AES


Fwd: [DMRN-LIST] Full-time PhD studentships

The School of Computing and Communications at the Open University (UK) invites applications for  full-time PhD studentships starting in October 2020. Studentships are for three years full time study, and cover tuition fees and a stipend.

The following topics are suitable, but you are welcome to propose a project in any area of music computing.

Musical Contrast (and Similarity)
Music and Emotion
Music and Narrative
Computational Creativity
Computational Musicology
Deep Learning for Music
Musical Pattern Discovery
Statistical Music Generation
Music for Computer Games/Multimedia
Collaborative Music Environments
MIR in Creative Settings

If interested, please contact me (Dr Robin Laney: robin.laney @ open.ac.uk) for an informal discussion and advice on constructing a proposal early, as a polished proposal will be needed.

Applications from part-time candidates also welcome.

Closing date to be set, but expect mid february.

The Open University is incorporated by Royal Charter (RC 000391), an exempt charity in England & Wales and a charity registered in Scotland (SC 038302).

Thursday, December 5, 2019

Fwd: Post-doc position on Music Ensemble Research



(Apologies for cross-posting. Please forward.)

Dear list,

we are happy to announce the opening of a post-doctoral position at the
Department of Music Acoustics – Wiener Klangstil (IWK) at the mdw –
University for Music and Performing Arts Vienna on empirical research on
togetherness in music ensembles.

More information:
https://www.mdw.ac.at/iwk/togetherness/

Best,
Werner

PS: A 3-year PhD position on the same project will be announced soon.

--
Dr. Werner Goebl
Associate Professor
Department of Music Acoustics – Wiener Klangstil
University of Music and Performing Arts Vienna
Anton-von-Webern-Platz 1
1030 Vienna, Austria
http://iwk.mdw.ac.at/goebl

Fwd: CfP Empirical Musicology Review: Special Issue on Open Science in Musicology


Dear colleagues,

We would like to draw your attention to two calls for the journal Empirical Musicology Review.


Empirical Musicology Review: Special Issue on Open Science in Musicology


Empirical musicology relies crucially on the creation, analysis, publication, and distribution of datasets. Despite the progress made over the past decades in this vibrating field, numerous issues regarding the sharing of data, the reproducibility of research findings, and the general role of transparency remain challenging. In many disciplines, these issues are addressed under the umbrella of the Open Science movement and the adherence to FAIR principles for scientific data management (findable, accessible, interoperable, reusable; https://www.go-fair.org/fair-principles). To advance the state-of-the-art in data-based music research, Empirical Musicology Review is devoting a special issue to a wide discussion of questions related to Open Science and Open Data, and introduces a new section on data reports that will remain a permanent part of the journal in all subsequent issues.


CfP: Research Articles and Think Pieces


We invite papers that address general aspects of Open Science / Open Data, discuss challenges in the application of the FAIR principles to music research, or reflect upon methodological and meta questions. Papers may also describe the generation of particular datasets and explore their characteristics in the context of the overall topic of this special issue. 

We envisage to include contributions from a wide variety of domains, such as music theory, music psychology, music information retrieval, historical musicology etc. The data must be accessible in an open repository or database. Papers should be 3000–6000 words in length.


CfP: Data Reports


Starting with this special issue, EMR is introducing a new section on Data Reports. In order to promote Open Science and to facilitate reproducibility, empirical studies of music are increasingly relying on openly available corpora and datasets. Since the scientific value of creating, cleaning, curating, enabling access, and maintaining data is of the utmost importance, EMR invites researchers to share their datasets and to apply the FAIR principles.

Data Reports may describe a variety of datasets such as musical metadata, annotations of musical corpora in symbolic or audio formats, automatically extracted musical features, data from psychological experiments etc. Data Reports should not exceed a word limit of 2000 words.


Please register on http://emusicology.org/ and submit your contribution by 31 March, 2020.


If you have any further questions, please get in touch with the guest editors:

Fabian C. Moss (fabian.moss@epfl.ch) and Markus Neuwirth (markus.neuwirth@epfl.ch)

Fwd: Music cognition/Music Therapy survey



Dear Colleagues,

You are warmly invited to participate in a brief survey study aimed at exploring the attitudes of those in the fields of music psychology and music therapy regarding interdisciplinary collaboration. The purpose of this research is to identify potential interest in these closely-related fields in the development of opportunities for interdisciplinary collaboration, as well as to explore current perceptions regarding the potential challenges and benefits of such collaborative work. The survey additionally includes demographic questions and several short personality assessments, to provide greater understanding of how interdisciplinary attitudes within our fields may vary in relation to such individual differences.

The survey takes approximately 20 minutes to complete. It can be accessed via this link:  https://www.surveygizmo.eu/s3/90184088/MPMT

Please do not hesitate to get in contact with any questions. Thank you for your time and your support for this project, and we look forward to sharing the results with you in the near future.

Kind Regards,

Emily Carlson, PhD
Centre for Interdisciplinary Music Research
University of Jyväskylä
emily.j.carlson@jyu.fi

Tuesday, December 3, 2019

Fwd: [DMRN-LIST] PhD studentships in Artificial Intelligence and Music (AIM) at Queen Mary University of London



UKRI Centre for Doctoral Training in Artificial Intelligence and Music (AIM), Queen Mary University of London
https://www.aim.qmul.ac.uk/

Up to 12 fully-funded PhD studentships to start September 2020
Covers fees and a stipend for four years
Application deadline: 31 January 2020

Why apply to the AIM Programme?
  • 4-year fully-funded PhD studentships available
  • Extensive choice of projects, drawing on a supervisory team of over 30 academics
  • Access to cutting-edge facilities and expertise in artificial intelligence (AI) and music/audio technology
  • Comprehensive technical training at the intersection of AI and music through a personalized programme
  • Partnerships with over 20 companies and cultural institutions in the music, audio and creative sectors
More information on the AIM Programme can be found at: https://www.aim.qmul.ac.uk/

Programme structure
Our Centre for Doctoral Training (CDT) offers a four year training programme where students will carry out a research project in the intersection of AI and music, supported by taught specialist modules, industrial placements, and skills training. Find out more about the programme structure at: http://www.aim.qmul.ac.uk/about/

Who can apply?
We are on the lookout for the best and brightest students interested in the intersection of music/audio technology and AI. Successful applicants will have the following profile:
  • Hold or be completing a Masters degree at distinction or first class level, or equivalent, in Computer Science, Electronic Engineering, Music/Audio Technology, Physics, Mathematics, or Psychology. In exceptional circumstances we accept applicants with a first class Bachelors degree who do not hold a Masters degree, provided that applicants can provide evidence of equivalent research experience, industry experience, or specialist training.
  • Programming skills are strongly desirable; however we do not consider this to be an essential criterion if candidates have complementary strengths.
  • Formal music training is desirable, but not a prerequisite.
For this round of applications we are offering a number of scholarships to applicants who are ordinarily resident in the UK (i.e. have lived and studied/worked in the UK at least the last three years - this includes EU nationals) and a smaller number of scholarships to international students.

Funding
We have a large number of 4-year PhD studentships available for students starting in September 2020 which will cover the cost of tuition fees and will provide an annual tax-free stipend  (£17,009 in 2019/20). The CDT will also provide funding for conference travel, equipment, and for attending other CDT-related events.

The AIM programme also welcomes applications from students who have sponsorship for PhD study from numerous international funding agencies and also accepts self-funded students. For more information on external PhD studentships and self-funded please visit http://www.aim.qmul.ac.uk/apply .

Apply Now
Information on applications and PhD topics can be found at: http://www.aim.qmul.ac.uk/apply
Application deadline: 31 January 2020
Application deadline for China Scholarship Council applicants only: 12 January 2020
For further information on eligibility, funding and the application process please visit our website. Please email any questions to aim-enquiries@qmul.ac.uk

--   Simon Dixon  Centre for Digital Music  School of Electronic Engineering and Computer Science  Queen Mary University of London  Mile End Road, London, E1 4NS, UK  http://www.eecs.qmul.ac.uk/~simond

Friday, November 29, 2019

Fwd: [DMRN-LIST] Job Announcement - Research Assistant at C4DM (Queen Mary Univ of London) - Cover Song Detection




The Centre for Digital Music (C4DM) at Queen Mary University of London
(QMUL) has a vacancy for a Postdoctoral Research Assistant (PDRA) in
music information retrieval, as part of the Innovate UK funded project
"Development of next generation music recognition algorithm for content
monitoring", in collaboration with Breathe Music Ltd.  The position is
available to start immediately and runs until 31 March 2021.

The responsibilities of the role are to investigate, develop and
evaluate machine learning and music information retrieval technologies
for automatically recognising alternative versions of a song
irrespective of the style in which it is being played – a problem also
known as musical work recognition or cover song detection. The work will
include evaluating existing methods for musical work recognition from
audio, proposing new methods, and developing software tools for the same
task.

See full details and how to apply here:
https://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwebapps2.is.qmul.ac.uk%2Fjobs%2Fjob.action%3FjobID%3D4874&data=02%7C01%7C%7Ccb8eb65598ef498afb9708d774d80a84%7C1faf88fea9984c5b93c9210a11d9a5c2%7C0%7C0%7C637106343541719088&sdata=jPBO6QW5E1elGQLQEcQqQbfkgyFbY5x5rqjs0zN%2BdDQ%3D&reserved=0

Applicants must be able to demonstrate the right to work in the UK.

Cheers

Simon

--
Simon Dixon
Centre for Digital Music
School of Electronic Engineering and Computer Science
Queen Mary University of London
Mile End Road, London, E1 4NS, UK
https://eur01.safelinks.protection.outlook.com/?url=http:%2F%2Fwww.eecs.qmul.ac.uk%2F~simond&data=02%7C01%7C%7Ccb8eb65598ef498afb9708d774d80a84%7C1faf88fea9984c5b93c9210a11d9a5c2%7C0%7C0%7C637106343541719088&sdata=u7a%2F76kV7VagOX1txSlb9dANSqgcrdiAdG0EJsGpUts%3D&reserved=0


Tuesday, November 19, 2019

Fwd: FW: Human Resources Advertisement - Post Doctoral Researcher in Participatory/Arts-Based Migrant Health Research (0.5 FTE)


Subject: post Doctoral Researcher in Participatory/Arts-Based Migrant Health Research (0.5 FTE)

 

The University of Limerick (UL) with over 15,000 students and 1,400 staff is an energetic and enterprising institution with a proud record of innovation and excellence in education, research and scholarship. The dynamic, entrepreneurial and pioneering values which drive UL's mission and strategy ensures that we capitalise on local, national and international engagement and connectivity. We are renowned for providing an outstanding student experience and employability and conducting leading edge research. Our commitment is to make a difference by shaping the future through educating and empowering our undergraduate and postgraduate students. UL is situated on a superb riverside campus of over 130 hectares with the River Shannon as a unifying focal point. Outstanding recreational, cultural and sporting facilities further enhance this exceptional learning and research environment.

 

Applications are invited for the following position:

 

Faculty of Arts, Humanities & Social Sciences

 

Irish World Academy of Music & Dance

 

Post Doctoral Researcher in Participatory/Arts-Based Migrant Health Research (0.5 FTE) – Specific Purpose Contract

 

Salary Scale: €37,874- €49,048 p.a. pro rata (maximum starting salary €41,373 p.a. pro rata)

 

Further information for applicants and application material is available online from: http://www.ul.ie/hrvacancies/

 

The closing date for receipt of applications is Tuesday, 26th November 2019.

 

Applications must be completed online before 12 noon, Irish Standard Time on the closing date.

 

This position is subject to Garda Vetting and Foreign Police Clearance. If you have resided outside Ireland for a cumulative period of 36 months or more over the age of 18 years you must furnish a Foreign Police Clearance (FPC) from the country or countries of residence. Please note; any costs incurred in this process will be borne by the candidate.

 

Please note your application must include:

 

A letter of introduction indicating how you meet the criteria outlined in the Job description.

A completed online Application Form (separate application forms must be submitted for each post applied for).

 

Please email erecruitment@ul.ie if you experience any difficulties

 

Applications are welcome from suitably qualified candidates.

The University of Limerick holds a Bronze Athena SWAN award in recognition of our commitment to advancing equality in higher education. The University is an equal opportunities employer and is committed to selection on merit welcoming applicants from all sections of the community. The University has a range of initiatives to support a family friendly working environment, including flexible working.

 

"The University of Limerick has implemented a "Smoke and Vape Free Campus Policy".  Smoking and vaping in all forms is prohibited."

 

HR excellence in research     Image result for ECU Gender Charter Logo    

 

    HRI logo   N&M logo               GEMS logo                    Doras Logo

 

Wednesday, November 13, 2019

Fwd: [DMRN-LIST] Funded Interdiscilnary PhDs in Musical Machines, Feedback Musicianship and Robot Opera - Jan 31st deadline


The University of Sussex invites applications for PhD studentship awards within its Leverhulme Doctoral Scholarship Programme entitled "From Sensation and Perception to Awareness", directed by Jamie Ward and Anil Seth.

The prestigious Sussex Leverhulme Trust Doctoral Scholarship Programme brings together doctoral researchers from different disciplines to advance our understanding of the interactions between sensing, perception, and awareness in humans, animals, and machines. The Programme will support an intake of up to NINE students starting in September 2020. PhD students will be registered within one of the participating schools (Life Sciences, Informatics, Psychology, Media Film & Music, and Brighton and Sussex Medical School). The closing date for applications is January 31st, 2020. For further details, including how to apply, see…

https://www.findaphd.com/phds/program/studentships-available-from-the-university-of-sussex-s-leverhulme-doctoral-scholarship-programme-from-sensation-and-perception-to-awareness/?i356p3783


 31st January for closing date and 24+25 Feb for interviews.



Investigating Feedback Musicianship

Supervisors: Dr Chris Kiefer, C.Kiefer@sussex.ac.uk  & Dr Alice Eldridge alicee@sussex.ac.uk

Apply to the School of Media, Film and Music

There is a growing interest in the creation of and performance with feedback instruments, musical instruments which are characterised by the recurrent circulation of signals, leading to non-linear and complex system dynamics (Eldridge and Keifer, 2017).  These dynamics create characteristic sonic outputs, and also mean that the more-or-less stable sensory-motor contingencies which underpin mastery of and performance with traditional instruments dissolve: there are dynamic, often unpredictable, rather than fixed relationships between physical gestures and sonic outcomes. These instruments possess 'a stimulation uncontrollability' (Ulfarsson 2019); compared to traditional performance practice, feedback musicianship is characterised by a more distributed agency between instrument and player.  Feedback instruments raise new questions around the nature of musician-machine interactivity, and provide a window into wider concerns of human engagement with real-world complex dynamical systems.  We welcome research proposals which investigate and advance our understanding of the experience of feedback musicianship; this could be approached through practice led research together with computational, psychological or physiological methods. Candidates should have an interest in and experience of the study of complex systems, a grounding in cognitive science and have experience in musical improvisation (in any idiom). A third supervisor will be sought according to the needs of the research proposal, in for example, philosophy, neuroscience or psychology.


Performing with Musical Machines

Supervisors: Prof Thor Magnusson, T.Magnusson@sussex.ac.uk

Apply to the School of Music, Film and Media

Recent developments in music technology and artificial intelligence have made the prospect of collaborating and performing with virtual and real musical machines actual. Our systems can learn, evolve and demonstrate creative behaviour. But how do we perceive these machines? How do we talk about computational creativity in its diverse manifestations? What language is emerging here regarding agency, authenticity and authorship? This project will develop series of experiments in robotic and virtual computational creativity and conduct related user studies. It will also engage in discourse analysis of how labs and companies around the world are presenting their creative technologies. The project is an interdisciplinary study with one foot in computer science and the other in the humanities.


Explorations in Robot Opera
Supervisor: Dr Evelyn Ficarra, E.J.Ficarra@sussex.ac.uk

Apply to the School of Music, Film and Media

The idea of using the performing arts as a laboratory through which to explore human – robot interaction (HRI) is gaining traction as a way of energising both the arts and the development of artificial intelligence.  Note, for example, the recent Performing Robots conference in Utrecht in May 2019, which repeatedly posited the idea of theatre as a 'test bed' for HRI explorations. Opera is a form which involves a high level of musical, theatrical and visual creativity. Experimental forms of opera, especially devised music theatre and improvisational forms, could therefore be the ideal HRI 'sand pit'. The abilities displayed by good musical / dramatic improvisers, for example (listening skills, a sense of timing and proportion, a commitment to team work, and ability to respond quickly and adapt to a changing situations, an ability to imaginatively co-create) could also be seen as transferable and highly prized social skills, in the development of AI. On the other hand, the influx of robotic and artificial intelligence technologies into the performing arts asks key questions about the nature and meanings of performance itself, as an augmented human experience. Which technologies will create the most compelling 'operatic' experience, and how might they re-define the form? Diverse proposals are welcome. Applicants should have a balance of expertise and/or strong interest in at least two of the following: music composition for opera or music theatre, robotics, music programming (e.g. of improvisational systems), artificial intelligence, machine learning, sensor driven technology.



--
Dr Alice Eldridge
Lecturer in Music & Music Technology
Co-Director Sussex Humanities Lab
University of Sussex
Falmer
Brighton
BN1 9RG

alicee@sussex.ac.uk
+44 (0)1273 877411
@alicealicealice
www.ecila.org