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considered a strong asset. Experience with Deep Learning and Artificial Intelligence is considered a plus. Excellent proficiency in the English language is required, as well as good communication skills, both
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related field with a strong quantitative focus. Strong programming skills in Python and demonstrated experience with machine deep learning frameworks (for instance, PyTorch or TensorFlow), preferably
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knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position We have a vacancy for a PhD candidate in machine learning
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knowledge, innovations, and solutions that help move the world forward. Faculty Mechanical Engineering From chip to ship. From machine to human being. From idea to solution. Driven by a deep-rooted desire to
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://www.academictransfer.com/en/jobs/363733/phd-candidate-multimodal-and-ag… Requirements Specific Requirements Profile We welcome candidates with an MSc or equivalent expertise in artificial intelligence, medicine, computer or
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IOCB Prague (Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences) | Czech | 3 months ago
bioinformatics or molecular biology position. We're looking for someone genuinely excited by the intersection of structural/molecular biology, physics-based simulation, and machine learning/deep learning – a
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journal or conference on a relevant topic in machine learning, embedded systems, and edge intelligence Hands-on experience on Nvidia Jetson boards or other edge platforms Strong knowledge in deep learning
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modeling, geometric deep learning or physics-informed machine learning, or you are willing to learn these quickly; strong collaboration skills: you enjoy working in a multidisciplinary team and feel
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or environmental engineering, Mathematics (Operations research) or Computer Science or Machine Learning). Documented knowledge of relevant methodologies, both quantitative and/or qualitative, at master’s level
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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 3 months ago
Approximations in Simulation-Based Inference*. Accepted at NeurIPS 2023. arXiv:2306.03580 L. Meyer, L. Poittier, A. Ribes, B. Raffin. *Deep Surrogate for Direct Time Fluid Dynamics*. Machine Learning and the