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to apply. We seek candidates with expertise in some or all the following areas: density functional theory, deep learning, high-throughput simulations, molecular dynamics, and materials chemistry. Strong
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of Artificial intelligence for De-Novo molecular design Machine learning/Neuronal networks to develop novel drug discovery tools Molecular modeling and simulation Theoretical biophysical medicinal chemistry Deep
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multidisciplinary team specializing in medical imaging and algorithm development. Our work focuses on advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities
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-based techniques (e.g., deep neural networks) will be used to automatically learn the system dynamics and the modelling errors, as well as to obtain an automatic tuning of the cost parameters/constraints
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Austrian Academy of Sciences, the Johann Radon Institute for Computational and Applied Mathematics (RICAM) | Austria | 15 days ago
, Approximation Theory, Machine Learning, Inverse Problems and Regularization Theory. Proficiency in programming with a strong preference for Python and deep learning frameworks such as PyTorch is highly desirable
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techniques such as yeast display and deep mutational scanning, or computational candidates with experience in generative AI, reinforcement learning, or agentic AI. The lab is supported by world-class
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, multimodal foundation models, continuous learning systems, or agentic AI models. Experience with state-of-the-art multimodal foundation models and agentic AI frameworks Experience in large-scale deep learning
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across the university. The RAD Collaboratory will be comprised of different research areas, each led by a faculty area lead. The vision of the RAD Collaboratory is “Deep Learning, Deep Connections
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(particularly Deep Learning), will also make it possible to leverage the collected data to enrich knowledge of ovine behavior. The candidate will join a dynamic research group within the Image/Vision team
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biologically-inspired deep learning and AI models (NeuroAI). The computational models we work with include vision deep learning models (including topographical, recurrent, or developmentally inspired models