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of molecular data. While machine learning has transformed fields such as computer vision and natural language processing, the molecular life sciences remain a rich frontier for methodological innovation
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, approaches related questions in an interdisciplinary manner (i.e., at the intersection of psychology, technology, and human–computer interaction). We welcome candidates with a strong interest in fundamental
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, biomedical engineering, medical technology, optics, mechatronics, computer engineering, or a related discipline. Strong motivation, scientific curiosity, and commitment to scientific excellence. Experience in
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. Become a part of our team and join us on our journey of research and innovation! Be
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of computer vision technologies. Be part of change Conduct research and development in the fields of Artificial Intelligence (AI) and Machine Learning (ML) Design, implement, and evaluate AI-based methods, with
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Engineering Computer Engineering Physics Mechatronics Information Engineering or a related field. Ideally, you have experience in several of the following areas: Electronic circuit or measurement system
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Max Planck Institute for Intelligent Systems, Stuttgart, Stuttgart | Stuttgart, Baden W rttemberg | Germany | about 2 months ago
, robotics, computer vision, and related disciplines. As the main doctoral program of the Max Planck Institute for Intelligent Systems (MPI-IS), IMPRS-IS brings together an international community of doctoral
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. As part of our project with the start-up testblu, we are looking for a Student
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infectious samples • Experience working with laboratory animals and in biosafety laboratories (BSL-2/3) • Strong communication skills in English, as our team is international • Solid computer skills, including
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, cavitation will be investigated both experimentally and via computer simulation. This doctoral project is a joint initiative between the Fraunhofer ITWM »Grid-Free Methods« Department and the Department