97 data-"https:"-"https:"-"https:"-"https:"-"BioData" positions at Aalborg University
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to the project, uniting experts in battery technology and acoustic signal processing and machine learning. The goal is to harness advanced data science techniques to establish a novel paradigm for online non
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, such as motion capture, electromyography, inertial measurement units, advanced data processing, numerical methods, optimization procedures, statistics, research ethics and management of personal data
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professional information from Associate Professor Kristian Olesen, Research Group of Planning for Urban Sustainability, 99407211, kristian@plan.aau.dk. Qualification requirements Appointment as assistant
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). Youmayobtainfurther professional information from Professor Malene Freudendal-Pedersen, Research Group of Planning for Urban Sustainability, 99402482, mfp@plan.aau.dk. Qualification requirements Appointment as
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, mechanical and durability testing, and integration with advanced machine learning models. The postdoc will collaborate closely with CEBE’s parallel work packages. Experimental and analytical data generated in
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Verification and Validation ; Data Engineering, Science, and Systems ; Distributed Sustainable Software and Systems ; Formal Methods for Security and Privacy ; Foundations for Interacting and Computing Systems
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of Computer Science has the following research groups: Automated System Verification and Validation ; Data Engineering, Science, and Systems ; Distributed Sustainable Software and Systems ; Formal Methods for Security
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of Computer Science has the following research groups: Automated System Verification and Validation ; Data Engineering, Science, and Systems ; Distributed Sustainable Software and Systems ; Formal Methods for Security
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for large-scale data collection and patient interaction. The position offers a unique opportunity to work at the intersection of biomedical engineering, app development, and health data science in a leading
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medical images and other health data. The group develops and evaluates clinically meaningful decision support tools by integrating health data, domain knowledge, and machine learning. Key objectives include