Con Espressione - Department of Computational Perception

Department of

Computational Perception

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OPEN RESEARCH POSITIONS IN ERC ADVANCED GRANT PROJECT
ON EXPRESSIVITY-AWARE COMPUTER SYSTEMS IN MUSIC
(Second Round; Aug. 2017)

We are pleased to announce several open research positions, at both PhD student and post-doctoral level, in two cooperating research groups in Austria:

the Department of Computational Perception of the Johannes Kepler University (JKU) Linz, and
the Machine Learning and Intelligent Music Processing and Machine Learning Group at the Austrian Research Institute for Artificial Intelligence (OFAI), Vienna.

The successful applicants will join the team of large five-year research project named "Con Espressione", funded by the European Research Council (ERC) in the form of an ERC Advanced Grant.

=> Read the Con Espressione Manifesto to learn about motivation for the project, and where your place and contribution could be!

Would you like to

contribute to the development of a new generation of musically intelligent systems that are aware of, and can recognise and manipulate, expressivity in music and in musical performances?
be part of one of the leading research groups in the fields of Music Information Retrieval (MIR) and computational music analysis?
make substantial original contributions to
- computational models of music segmentation, structure understanding, and musical expectation
- computational analysis and modeling of expressive music performance
- the analysis and characterisation of musical scores and recordings
- a new generation of MIR systems and applications
- expressivity-aware real-time music companions
by uniting methods and theories from musicology, probabilistic models, information theory, and machine learning?

Do you have

an academic degree (MS or PhD) in computer science, Artificial Intelligence, machine learning, musical informatics, sound and music computing, or related fields
a strong formal and musical background
prior experience in at least two of the following:
- machine learning
- deep belief networks and deep learning
- probabilistic models (Bayesian networks, HMMs, CRFs, ...)
- computer-based music analysis
- computational music performance modeling
- audio signal analysis and pattern recognition
- music information retrieval
a deep interest in (classical) music
(at least basic) knowledge of music theory and, most importantly:
a creative mind, and the courage/urge to address new, hard, exciting research questions?

Particular research topics in the focus of this call (possible PhD thesis topics):

Deep Learning Models of Emotion Recognition in Music
Deep Models of Musical Structure Recognition [symbolic scores / audio]
Deep Learning Models of Musical Expectancy and Surprise
Learning to Recognise Expressive Cues from Music Performances
Generating Expressive Performances with a Desired Expressive Intention
Expressivity-aware Real-time Accompaniment

If you find this interesting, consider applying for one of the following kinds of positions:

PhD student level:
- Duration: 3 years, with possibility to enrol in a PhD program
- Salary: approx. € 28.000,- to 38.000,- per year (before taxes)

Post-doctoral level:
- Duration: 1-2 years
- Salary: approx. € 50.000,- per year (before taxes)

Please send questions, application materials etc. by e-mail to Gerhard Widmer.