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Processing and Image Analysis Group, Section for Machine Learning, Department of Informatics. You will be part of Visual Intelligence and the DSB group. For more information about the position see https
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(iii) complex architectures with tightly coupled components hinder modular adaptation. To address these limitations, we research a physics-guided machine learning framework that integrates physical
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. The manager will develop an annual work plan in consultation with the two supervisors and is evaluated on the success of that plan. The Department of Engineering Education (http://www.enge.vt.edu) is home to
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public. • Ability to communicate effectively across cultural boundaries and work harmoniously with diverse groups. • Demonstrated ability to effectively teach electrical, robotics, or computer engineering
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the excellence cluster Your profile PhD in physics or in a related discipline experience in phase contrast or coherent X-ray imaging advanced programming skills in a high-level computer language (Python or related
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The Singapore Institute of Technology (SIT) is Singapore’s first University of Applied Learning and the third largest university by intake in Singapore. Our mission is to maximise the potential
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 14 days ago
machine learning, 3D visualisation and real-time images (augmented reality). The main robot will the Tiago++, by PAL Robotics, which is a modern omnidirectlonal, bimanual robot. With the help of a PhD
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Science, or Information Science. The position requires experience with at least one of the following: Data Science, Machine Learning, Computational Social Science, Big Data. Relevant skills could include statistical analysis, data
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application! We are looking for one or more PhD student(s) to the Division of Communication Systems at the Department of Electrical Engineering (ISY). Your work assignments Much of the traffic in 6G networks
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understanding of how acoustic waves are generated and transmitted in wells. The LeDAS project aims to overcome these challenges by combining physical modelling, advanced signal processing, and machine learning in