22 Dec 2022
Job Information
- Organisation/Company
- Universitat Pompeu Fabra - ETIC
- Department
- Tecnologies de la Informació i les Comunicacions
- Research Field
- Other
- Researcher Profile
- Recognised Researcher (R2)
- Country
- Spain
- Application Deadline
- Type of Contract
- Other
- Job Status
- Full-time
- Hours Per Week
- 35
- Offer Starting Date
- Is the job funded through the EU Research Framework Programme?
- European Union / Next Generation EU
- Is the Job related to staff position within a Research Infrastructure?
- No
Offer Description
We are looking for a Researcher/developer to join the team of the Music Technology Group to work on the creation, adaptation and testing of machine learning models applied to different sound and music industry use cases. The selected candidate will join the projecte AISMA: AI models for Sound and Music Application
- Assess and benchmark the existing commercial solutions and state of the art academic contributions which, based on ML models, address common sound and music tasks.
- Definition of use cases and data collection
- Build models using state of the art deep learning architectures that achieve high performance on the different selected use cases
- Validation of models in real-world use cases in collaboration with MTG’s industry partners
Main research field: Music Technology
Requirements
- Research Field
- Computer science » Other
- Education Level
- Master Degree or equivalent
Skills/Qualifications
Required skills and qualifications:
- Degree in Computer Science, Electrical Engineering or equivalent
- Master degree in Sound and Music Computing, Music Technology, or related field
- Experience in the design, development and testing of software
- Experience in Linux and Phython
- Ability to work and deliver autonomously while being a part of a team
- Fluent in English
- Languages
- ENGLISH
- Level
- Excellent
Additional Information
Eligibility criteria
Selection criteria:
- Formal education requirements (Degree in Computer Science, Electrical Engineering or equivalent. Master degree in Sound and Music Computing, Music Technology, or related field)
- Professional experience
- Experience related to the Music technology sector
Other preferred skills:
- Experience with Machine Learning and Deep Learning environments like TensorFlow and/or PyTorch
- Experience with managing large collections of data
Additional comments
The list of those admitted and excluded, as well as the hiring proposal, will be published on the website https://www.upf.edu/web/etic/managemen
Work Location(s)
- Number of offers available
- 1
- Company/Institute
- Universitat Pompeu Fabra - ETIC
- Country
- Spain
- City
- Barcelona
- Postal Code
- 08018
- Street
- Roc Boronat 138
Where to apply
- Website
Contact
- City
- Barcelona
- Street
- Roc Boronat 138
- Postal Code
- 08018
- recerca.etic@upf.edu