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and knowledge transfer. Discipline, including, but not limited to: Electronic and Information Engineering, Computer and Data Engineering, Electronic and Electrical Engineering, Information Engineering
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) Country United Arab Emirates Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position
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institution. At the Faculty of Computer Science, Institute of Artificial Intelligence, the Chair of Machine Learning for Computer Vision offers two full-time positions as Research Associate / PhD Student (m/f/x
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, or Full Professor) in the following areas: Machine Creativity: Computer graphics, computer vision, robotics, etc. Machine-assisted Art Practice: Visual, sound, performing, installation, cinematic arts, etc
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reliably stratify patients based on their fracture risk. The position is funded as part of Horizon 2020 European Project (https://www.metastraproject.eu/ ) that aims to provide a combination of models
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cutting-edge research in areas such as pattern recognition, automation science, complex systems, AI for Science, robotics, machine learning, computer vision, natural language processing, biometrics, medical
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specialism in Macroeconomics, Finance or Applied Econometrics. You will be qualified to PhD level and have teaching experience, and will make a key contribution to the School’s research-led teaching curriculum
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and will hold office hours as appropriate. Qualifications: PhD in bioinformatics, biology, or a closely related field. Experience with the application of computational methods to biological problems
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Computer Science, MD degree, or related field. Experience and Skills: Experience in image or signal processing, medical data processing, artificial intelligence and/or computer vision. Basic system administration
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Computer Science, MD degree, or related field. Experience and Skills: Experience in image or signal processing, medical data processing, artificial intelligence and/or computer vision. Basic system administration