Open Positions
January 2024 (Open)
Opportunity in Deep Learning Research for Neurodegenerative Disorders.
We are pleased to announce open positions for Postdocs and/or PhD students to engage in cutting-edge deep learning research. The primary focus of this project is the use of speech as a biomarker for early detection of neurodegenerative disorders, particularly Parkinson's disease. This research initiative is part of the highly cross-disciplinary project, bringing together deep learning experts, neuroscientists, neuropsychologists, and specialists in communication and speech disorders.
Project Overview: This project presents a unique opportunity to work with a substantial dataset comprising speech samples, medical images, and patient medical records. The collaboration of diverse expertise aims to advance our understanding of neurodegenerative disorders and contribute to the development of innovative diagnostic tools.
Academic Affiliation: Successful candidates will be enrolled either at McGill University or Concordia University (Department of Computer Science and Software Engineering). The position is also linked to The Centre for Research on Brain, Language and Music (CRBLM) and the Mila-Quebec AI Institute. Additionally, candidates can actively contribute to the SpeechBrain project.
Supervision: Students will benefit from the guidance of Prof. Mirco Ravanelli (Concordia University and Mila-Quebec AI Institute) and Prof. Denise Klein (McGill University, Director, Centre for Research on Brain, Language and Music).
April 2022 (Closed)
We have several open PhD positions on deep learning for conversational AI, speech technologies, and more generally machine learning for sequence processing.
We expect the candidates to do research on deep learning topics such as self-supervised learning, cooperative deep learning, continual learning, multi-task learning, small-footprint models, graph neural networks, deep generative models, out-of-distribution generalization. Potential projects include, but are not limited to:
Self-supervised representation learning for speech and audio.
Conversational AI technologies that can be used in personal assistants.
Speech enhancement and separation under real-life conditions.
End-to-end speech based meeting analysis (speech diarization).
Multi-task representation and metric learning for speech technologies.
Life-long/continual learning for personal assistants.
Deep generative models for speech/audio synthesis.
Cooperative systems with graph neural networks.
Deep learning for dialogue systems.
The students will be supervised by Prof. Mirco Ravanelli and will earn a doctorate degree in Computer Science from Concordia University (Department of Computer Science and Software Engineering, part of the Gina Cody School of Engineering and Computer Science).
The positions will be filled soon. Please apply as soon as possible.
More information here.
March 2022 (Closed)
Prof Hassan Rivaz and I have a joint position for a PhD student working at Concordia University in the area of deep learning in ultrasound imaging.
We are looking for an excellent student with the following requirements:
- Masters in CS, ECE, BME or a relevant field
- Excellent background machine learning and deep learning
- Excellent programming skills
The position will be filled by the end of March 2022. Please apply as soon as possible.
More information here.