Researcher For Ai Methodologies Of Interest For Music Distribution | (C274)

Detalles de la oferta

Offer Description Researcher for carrying out scientific and technical activities for the research line of new AI methodologies of interest for music distribution.
- Train and co-supervise doctoral and master's students who develop their doctoral thesis in Music and AI within the framework of the AI and Music Chair.
- Conduct research that allows the development of new AI methodologies based on deep learning supporting the different processes involved in music distribution.
- Coordinate the development of software that implements the results of basic research.
Specifically, extend the Essentia software library with more audio processing algorithms and more deep learning models useful for music creation, production, distribution, and education.
- Coordinate the development of prototypes to demonstrate the software and datasets developed.
- Promote technology transfer based on open innovation processes.
Strengthen contracts with companies.
Requirements Research Field: Engineering Education Level: PhD or equivalent Skills/Qualifications GENERAL Be in possession of the Doctor's degree.
Not having been separated by means of a disciplinary file from the service of any of the public administrations, nor having been disqualified by a final judgment for the performance of public functions.
In the case of being a national of another country, not being disqualified or in an equivalent situation or having been subjected to a disciplinary or equivalent sanction that prevents, in their State, access to public jobs in the same terms.
Specific Requirements Doctorate in engineering, computer science or related fields.
Regulated studies with specialization in music technology.
Research experience in the fields of signal processing and machine learning.
Experience in the design and implementation of audio analysis algorithms, as well as the management of large data collections.
Experience in supervising doctoral students.
Experience in technology transfer activities in relation to companies in the music distribution sector.
Languages ENGLISH Level: Excellent SPANISH Level: Excellent Years of Research Experience: More than 10 Additional Information Work Location(s) Company/Institute: Universitat Pompeu Fabra - Department / School of Engineering Country: Spain State/Province: Barcelona City: Barcelona Postal Code: 08018 Street: Roc Boronat 138 Contact E-Mail: ****** #J-18808-Ljbffr


Salario Nominal: A convenir

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