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L'ÉTS vous donne rendez-vous à sa journée portes ouvertes qui aura lieu sur son campus à l'automne et à l'hiver : Samedi 18 novembre 2023 Samedi 17 février 2024 Le dépôt de votre demande d'admission à un programme de baccalauréat ou au cheminement universitaire en technologie sera gratuit si vous étudiez ou détenez un diplôme collégial d'un établissement québécois.

Événements à venir

Quantum inspired machine learning and spiking neurons

Programme d'études visé
Postdoctorat
Domaines de recherche
Les systèmes intelligents et autonomes
Financement
2 years, competitive salary.
Autres informations

Date de début du projet: Dès que possible

Partenaire impliqué : Dr. Sellier à GAIA, Ericsson Montréal

Autre personne contact: Bassant Selim, professeure, bassant.selim@etsmtl.ca

Personne à contacter

Applications are invited for a post-doctoral researcher in quantum-inspired machine learning for applications in telecommunications. The candidate will work under the supervision of Prof. Granger and Prof. Selim at the Laboratory of imaging, vision and artificial intelligence (LIVIA), ETS Montréal (University of Québec), and in collaboration with Dr. Sellier at Ericsson Montreal. This funded position is available immediately for two years and offers a competitive salary. It also offers a possibility for collaborations/internships with top research companies and institutions in Montreal and abroad. We are looking for a highly motivated post-doctoral fellow interested in performing cutting-edge research on machine learning algorithms applied to relevant problems issued from the field of telecommunications, with a particular focus on spiking neural networks and supervised learning.

Connaissances requises

Prospective applicants should have the following profile:
• strong academic record with an outstanding doctorate in computer science,
applied mathematics, applied physics, or electrical engineering, preferably with expertise in one or
more of the following areas: machine learning, training methods, pattern recognition, quantum mechanics, artificial intelligence;
• good applied mathematical and physics background;
• very good knowledge of English
• good programming skills in the C language (C99), with possible knowledge of parallel computing (OpenMP) and deep learning frameworks;
• strong publication record in significant conferences or journals in machine learning or applied physics.