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Research Assistant in Machine Learning with Audio

8 days ago | Closing on Nov 25
Aalto University
Research Assistant in Machine Learning with Audio
Aalto University
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JOB DETAILS
Published: 8 days ago
Application deadline: Nov 25
Location: Espoo, Finland
Please mention that you found this job on Academic Positions when applying.
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Research Assistant in Machine Learning with Audio

Aalto University is a community of bold thinkers where science and art meet technology and business. We are committed to identifying and solving grand societal challenges and building an innovative future. Aalto University has six schools with nearly 20 000 students and more than 400 professors.

The School of Arts, Design and Architecture (ARTS) is an institution of higher education for design, media, architecture, motion picture, art education and art. The current key areas of research are design, digital media, audiovisual representation, art, visual culture, welfare architecture and emerging technologies as well as urban planning and design. The school produces specialists and innovators of art, design and architecture with strong artistic and technical skills.

The Department of Media is looking for a full time or part time (50%)

Research Assistant in Machine Learning with Audio

We are looking for 1 full time or 2 part time student assistants to help us to prepare teaching materials for the Intelligent Computational Media course which will give opportunity to Game and Sound in New Media students in Aalto ARTS to get familiarise themselves with overall models of networks behind deep learning and Artificial Intelligence. The students will use these teaching materials to work on the course exercises as well as to build their artistic, design, game and sound projects.

The position is fixed-term for three months, expected starting day is 3.12.2018 but it is negotiable.

Main duties and responsibilities

The research assistant will prepare the course materials described in detail below :

  • The first teaching material will provide algorithm for Audio Style Transfer, extending the process of image style transfer to audio. Parag Mital already published the initial code and models (https://github.com/pkmital/time-domain-neural-audio-style-transfer), we would like to use this algorithm and extend time domain model further with possibilities to perform in real time, specifying different input features as well as make this approach to perform more successful stylisation.
  • In the second teaching material we would like to perform style transfer with CycleGAN model in audio domain. Similar to the previous template, this exercise will apply the process of image style transfer to audio but students will prepare their own datasets and train the CycleGAN audio model. We are aiming to develop this exercise further to give possibilities to students to use the pre-trained checkpoints in their real-time artistic performances/projects. 
  • The final teaching material will focus on Magenta Google NSynth modules (https://github.com/tensorflow/magenta/tree/master/magenta/models/nsynth) as described in NSynth, the teaching material will use WaveNet-style autoencoder model to explore new control possibilities over "timbre and dynamics and the ability of creating new sounds".

Please check the initial teaching material we prepared using WaveGan module for this course, which highlights our expectation for the above  - https://github.com/SopiMlab/MachineLearningWithAudio/blob/master/Documentation/UsingWavegan.md, https://github.com/SopiMlab/MachineLearningWithAudio/tree/master/Documentation

Key selection criteria

  • Bachelor's or Master's student in computer science, design studies or another relevant field in a Finnish university
  • Hands-on programming skills: advanced knowledge in Python
  • Experience in machine learning 
  • Basic Knowledge in Digital Audio
  • Basic Knowledge in C++ is considered as an advantage but is not required
  • Ability for collaborative work in research-related contexts
  • Excellent skills in English language

Salary

The monthly salary will be paid according to the University’s salary scheme. The position will be located at Aalto ARTS’s new building Väre in Aalto University metro station, Otaniemi, Espoo.

How to apply

Applications for the positions require:

  1. CV
  2. Most recent academic transcript from your university (digitally signed is accepted)
  3. Example(s) of a relevant research/design projects in machine learning or/and projects implemented by Python

Please submit the material in English, in PDF format through the eRecruitment system no later than on 25th of November 2018. Please name all your documents according to for example Lastname_Firstname_CV.pdf.

Aalto University reserves the right, for justified reasons, to leave the positions open, to extend the application period, and to consider candidates who have not submitted applications during the application period. The application materials will not be returned.

For additional information, please contact Academy Research Fellow Koray Tahiroglu, or in recruitment process related questions, HR Coordinator Ilona Kallio; both emails: firstname.lastname@aalto.fi.
 

Living up to our values As a community of high ethics we want to assure the highest international standard  in research, education and teaching. We expect all our community members to respect Aalto values and follow the ethical principles of fair play and integrity in all our activities and the behavior that we expect from each other. Aalto University Code of Conduct is applicable to all Aalto community members and it clarifies the values that guide us.

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