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quantified, and machine learning will be used. Duties As a PhD student, you will work toward a doctoral degree as the final goal, according to the goals specified in the Higher Education Ordinance. In parallel
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leveraging visual perception of human actions, object properties, and scene context. It integrates machine learning tools, knowledge representation, and robot actions design to develop decision-making
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Chemistry (experimental/computational physical chemistry) -Transition metal photocatalysts studied by femtosecond X-ray science with a focus on hybrid experimental/machine-learned structural dynamic analyses
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Do you have a background in deep learning and computer vision? Are you
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: www.uni.lu/snt-en/research-groups/finatrax/ The candidate will be enrolled in the PhD program in Computer Science and Computer Engineering with specialisation in Information Systems. In the context of Prof
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Do you have a background in deep learning and computer vision? Are you independent, creative and eager to take initiatives? Do you enjoy working in an international research group and interacting
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with, cloud computing and virtualisation technologies Familiarity and hands-on experience with machine learning techniques desirable Desirable to have work experience (through internships or similar) in
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for computationally demanding applications and machine learning. - Good analytical skills and a positive attitude towards interdisciplinary work. Additional Information Benefits We offer you, following the Collective
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at the interface of microbial ecology and advanced analytical technology. In our laboratories we have state-of-the art 3D printers and CNC machines as well as NMR spectrometers. Key responsibilities: Design and
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off-the-shelf sensors and the development of resilient algorithms that combine first-principles modeling with modern machine learning techniques. The goal is to push the boundaries of robust perception