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in machine learning, AI and programming skills, e.g. Python basic knowledge of materials science / materials engineering Leibniz-IWT is a certified family-friendly research institute and actively
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | about 2 months ago
holography. We are seeking a highly motivated postdoctor-al researcher to join our multidisciplinary team at the intersection of optics, electronics, machine learning, and atmospheric science. The successful
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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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experience in the analysis of metagenomics and/or biological high-throughput data Knowledge of statistical and machine learning methods in the context of biological systems Experience with programming (e.g
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)! Tübingen has a long history of academic excellence (founded in 1477; DNA was discovered here ; linked to 11 Nobel laureates) and is an innovation center in medicine and machine learning. About Eberhard
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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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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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planning and control algorithms Multi-modal perception techniques (e.g., vision, tactile, force) Machine learning models for physical behavior prediction and manipulation strategy adaptation Real-world
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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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, Computer Science or related fields (for PhD); Doctorate in Physics, Computer Science or related fields (for Post-Docs). The positions are funded via the Cluster of Excellence (Machine Learning for Science), the ERC