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teaching duties. Requirements: Applicants should possess a PhD degree in Computer Science, Computer Engineering, Information Systems, or a related field, and sufficiently demonstrate abilities to conduct
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Machine Learning; (ii) Big Data and Data Management; (iii) Computer Vision and Pattern Recognition; and (iv) Distributed Systems and Networking. These key research areas have a special thematic focus on (a
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programme. Further information about the IAC's research programme, its Observatories and the 10.4m GTC is available at the IAC's web page: https://www.iac.es/en Tasks:The successful candidate will pursue
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well as innovative and inquiry-based teaching and learning. The Faculty consists of six departments as well as a Faculty administration. Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/296312/phd
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) Developing machine-learning based exoskeleton controllers to work across tasks 2) Designing and validating new robotic lower-limb prostheses 3) Exploring other high-risk high-reward research areas related
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spoken English. Who we are The Department of Electrical and Computer Engineering is one of four engineering departments at the Faculty of Technical Sciences at Aarhus University. Our vision is to be a
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to SAFE. Delivering EVU course from SAFE center. Required selection criteria A PhD degree (or equivalent) in biometrics, information security, computer science, electrical engineering, or machine learning
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ICT Services & Applications. Your role We offer a fully funded PhD student position within the TruX Research Group headed by Prof. Dr. Tegawendé F. Bissyandé. The position is supported by Google.org and
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that support the unit for area protection and marine spatial planning, as well as operations at SLU Aqua. Your profile You have documented expertise in marine ecology and computer vision and machine learning
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. Your profile You have documented expertise in marine ecology and computer vision and machine learning methods for video-based fish monitoring. You have excellent IT skills and experience in handling