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(PyTorch, Tensorflow etc.) Knowledge of multi-agent systems and autonomous agent modelling Expertise in Machine Learning and Artificial Intelligence We consider the following as an advantage: Willingness
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Description The Clinical Artificial Intelligence Lab at NYU Abu Dhabi seeks to improve patient care by developing new machine learning methodologies that tackle unique computational problems in
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: 278964401 Position: 2025 Postdoctoral Research Associate - AI/machine learning for analytical and forensic chemistry Description: The Skinnider Lab at Princeton University aims to recruit a postdoctoral
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handling Experience with data analysis and neuronal recordings Experience with visual discrimination experiments on mice Experience with machine learning techniques and neural network modeling Evaluation
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industrial partner, you will design and implement innovative architectures for real-time detection and control of laser processes. This interdisciplinary role combines artificial intelligence and machine
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and refined our pioneering AI-driven methods. This project focuses on improving protein structure prediction, design, quality assessment, and dynamics using innovative machine learning techniques. You
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think outside the box, to learn fast, collaborate effectively, iterate quickly, and work at the interface of both experimental and computational design. Qualifications for Computer Scientists, AI/ML: PhD
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Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg | Magdeburg, Sachsen Anhalt | Germany | 6 days ago
the microbial metabolism, with applications in metabolic engineering and bioprocess optimization. Your tasks For two interdisciplinary research projectsin the field of computer-aided metabolic engineering, we
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qualifications: PhD or equivalent achievement (proof of independent research capability) in Machine Learning, Computer Science, Physics, Mathematics, or a related field Deep theoretical knowledge and extensive
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engineering, or related disciplines who are passionate about applying machine learning to real-world clinical challenges. The successful candidate will lead the development and validation of predictive models