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Field
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machine learning methods based on specific problems The targeted visualization of results is also within your area of responsibility What you bring to the table You are studying physics, mathematics
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is connected to the vibrant local ecosystem for data science, machine learning and computational biology in Heidelberg (including ELLIS Life Heidelberg and the AI Health Innovation Cluster ). Your
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Tübingen offers a combination of high-performance medicine and strong research. The goal of the Carl-Zeiss-Project “Certification and Foundations of Safe Machine Learning Systems in Healthcare” is to enable
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mining and machine learning Leibniz-IWT is a certified family-friendly research institute and actively pursues equality for all groups of people. We promote the professional development of women
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civil/electrical/control engineering or mathematics or related study programs with a solid basis in choice modelling and/or reinforcement learning, with knowledge of MATSim is advantageous. Description
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reduction, uncertainty quantification, machine learning, fluid mechanics. Experience with scientific object-oriented programming languages (C++, Python, or Julia) is highly relevant. Knowledge
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Photonic Networks and Systems department is conducting research on the next
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control software and machine learning expert. How you will support us: ▪ You will take on responsibilities in the field of control and operation of high-coherence superconducting quantum circuits, with a
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science (for example, but not limited to, data science, machine learning, statistics, computer science, mathematics, etc.) acceptance by a PhD supervisor with examination admission for PDS and formation
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community around machine learning of the SCADS.AI center (https://scads.ai ) and the recently granted Excellence Cluster REC² – Responsible Electronics in the Climate Change Era. We aim to attract the best