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Post-doctoral position in Computer Vision/Machine Learning (3D object Recognition, Pose Estimation, Augmented Reality). Ryerson University in Toronto

The Ryerson Multimedia Research Laboratory at Ryerson University in Toronto, Canada is seeking a highly motivated and creative postdoctoral candidate to engage in innovative research in augmented reality, with primary focus on creating novel vision-based 3D object recognition and pose estimation algorithms utilizing recent developments in deep learning, with a focus on computational efficiency.
The goal of the position is to collaborate with a team of researchers (PhD, Master’s students and Research Assistants) to develop state-of-the-art deep learning techniques to perform real-time 3D object recognition and simultaneous pose estimation. The end-goal is to create e cloud-based framework that can deliver the object recognition and pose estimation results to mobile devices, enabling intelligent AR experience design.
The position will be for one year, renewable upon satisfactory performance and subject to availability of research funds. The starting date is flexible but would preferably begin on October 1, 2018. The salary range is $45,000 to $55,000 CAD per annum plus benefits and will be determined by the experience and qualifications of the candidate. (Click here for information about the benefits.)
The position will be funded by an NSERC Collaborative Research and Development (CRD) grant. The fellow is expected to work closely with the industry partner to ensure that the requirements of the CRD project is being fulfilled.
The successful candidate will be a member of and work with a team of researchers at the Ryerson Multimedia Research Laboratory. The incumbent is expected to be in Toronto during the tenure of this position.

RESPONSIBILITIES:

The postdoctoral fellow will be expected to collaborate actively with all team members. These responsibilities include, but are not limited to:
• Do extensive literature review on learning-based 3D object recognition and pose estimation, specifically identifying research gaps in computational optimization of such methods for mobile devices.
• Implement research ideas with open source libraries (Keras, TensorFlow, PyTorch).
• Distribute and manage software development tasks among team members as necessary.
• Participate in research paper writing, publication, and presentations at different venues.
• Maintain regular communication with industry partner and provide regular update on research progress.

QUALIFICATIONS:

• A doctorate in Computer Science/ Electrical and Computer Engineering/ related field is required.
• Strong computer vision and/or machine learning background.
• Hands-on experience with computer vision/deep learning tools and techniques (Keras, TensorFlow, PyTorch, MATLAB or similar).
• Experience with cloud-based prototype development.
• Excellent English writing skills.

DESIRABLE QUALIFICATIONS:

• Strong Publication record in field of expertise.
• Some mobile application development experience.
• Some Unity3D development experience.

HOW TO APPLY:

Candidates should submit the following materials electronically to Dr. Naimul Khan at n77kan@ryerson.ca:
• Cover Letter that describes your relevant background and skills, range of interests and career goals.
• Academic CV.
• The name and contact information for two research references (one reference should be your doctoral advisor).
• At least 2 relevant publication samples.

DEADLINE:

Review of applications will begin on September 1, 2018 and continue until the position is filled.

INSTITUTIONAL BACKGROUND:

Located in the heart of downtown Toronto, the largest and most culturally diverse city in Canada, the Ryerson Multimedia Research Laboratory is an internationally recognized lab which focuses on three key research areas: machine learning, computer vision, and multimedia signal processing. RML has several industry and academic partners with whom the lab members work on solving critical research issues such as: object recognition, tracking, segmentation, action recognition, 3D reconstruction, optimal resource allocation, multimodal information fusion, etc.
Ryerson University is a public research university. The university is composed of 36,000+ undergraduate students, 2,000+ graduate students, and 70,000 yearly certificate and continuing education registrations. Ryerson has been one of the fastest growing research institutions in Canada. Ryerson University is committed to diversity, equity and inclusion. The university is known for innovative programs built on the integration of theoretical and practically oriented learning.

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