Seeking an outstanding established scholar or emerging researcher for the Gina Cody Research Chair in Computer Science. The successful candidate will be appointed into a full-time position at the rank of Assistant, Associate or Full Professor. The ideal candidate is either an internationally recognized researcher with an exceptional scholarly record who has proven leadership qualities, or an emerging researcher with the potential to be a leader in their field. The candidate is expected to demonstrate a commitment to the supervision of master’s and PhD students and attract strong external funding. The five-year research chair is renewable and comes with an attractive research funding package.
The main criteria for selection are scholarly and teaching excellence. The successful candidate is an established or emerging researcher, with a demonstrated ability or evidence to attract strong external funding, and to carry out an independent research program leading to high-impact publications. Industry experience or applications of research to industry will be considered an asset.
The department values diversity among its faculty and strongly encourages applications from women and members of underrepresented groups.
Additional info: https://www.concordia.ca/ginacody/about/jobs/csse/2021/gina-cody-research-chair-computer-science.html
All qualified candidates are encouraged to apply; however, Canadian and Permanent Residents will be given priority. To comply with the Government of Canada’s reporting requirements, the University is obliged to gather information about applicants’ status as either Permanent Residents of Canada or Canadian citizens. While applicants need not identify their country of origin or current citizenship, all applications must include one of the following statements: “Yes, I am a citizen or permanent resident of Canada.” or “No, I am not a citizen or permanent resident of Canada.”
Language of instruction | Langue d'enseignement:English
Position type | Type de poste:Research & teaching | Recherche et enseignement
Research and/or teaching fields | Domaines de recherche et/ou d'enseignement:artificial intelligence, machine learning, deep learning and reinforcement learning, quantum computing, quantum machine learning, software design, natural language processing, computer vision, robotics, medical imaging, computer graphics, computer games, computational models and algorithms, databases and big data analytics, high performance computing, financial computing and analytics
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