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Field
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metrics. - Uso de técnicas de aprendizaje máquina/profundo y técnicas de segmentación aplicado al procesamiento de imágenes y vídeo / - Use segmentation and machine/deep learning techniques applied to image
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that attracting and sustaining a diverse workforce is key to the successful pursuit of excellence in research, innovation, and learning for all faculty, staff and students. Our commitment to employment equity helps
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knowledge of Python Interest in AI, machine learning, or game design Ability to work independently and meet milestones Modes of Work Positions that are eligible for hybrid or mobile/remote work mode are
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de técnicas de aprendizaje automático (ML/DL) aplicado a imágenes. / Proven experience in the use of machine learning techniques (ML/DL) applied to images. Experiencia demostrable en el desarrollo de
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programming language. Does this position have supervisory responsibilities? No Preferred Education/Experience B.S. in Anthropology, Computer Science, or related fields; experience with digital mapping, GIS
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making and machine learning, with real-world testing and feedback. The successful applicant will work on decision making for anomaly detection, behaviour analysis and surveillance decisions, under
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tools and computer programs to review data. Assist with data cleaning measures to ensure accuracy of data and preparation of tables. Lead basic activities such as data collection and data entry. May lead
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background in AI—such as knowledge of machine learning or neural networks—will be an advantage. The appointee is expected to conduct focused research, publish scholarly outputs in reputable, peer-reviewed
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, timely, and thorough. Works well both independently, with little supervision, and in a team setting. Knowledge of genetics and genetic concepts or desire to learn. Strong computer skills and experience
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background in AI—such as knowledge of machine learning or neural networks—will be an advantage. The appointee is expected to conduct focused research, publish scholarly outputs in reputable, peer-reviewed