This event focuses on a forthcoming online training course titled “Deep Learning—Fundamentals and Applications to Examples in Materials Science,” scheduled for February 24-28, 2025. Organized by experts from Saarland University and the Material Engineering Center Saarland, the course aims to provide professionals in materials science, R&D, digitization, and AI with practical knowledge and hands-on experience in deep learning techniques. Participants will explore the use of tools such as PyTorch and Jupyter Notebook to implement neural networks for image and tabular data analysis, gaining skills in classification and segmentation. The program emphasizes addressing real-world challenges with expert guidance and awards a certificate of completion, enhancing participants’ expertise and contributing to their organization’s competitiveness in leveraging AI for materials science innovation.
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In general, if you enjoy reading this kind of scientific news articles, I would also be keen to connect with fellow researchers based on common research interests in materials science, including the possibility to discuss about any potential interest in the Materials Square cloud-based online platform ( www.matsq.com ), designed for streamlining the execution of materials and molecular atomistic simulations!
Best regards,
Dr. Gabriele Mogni
Technical Consultant and EU Representative
Virtual Lab Inc., the parent company of the Materials Square platform
Website: Home | Virtual Lab Inc.
Email: gabriele@simulation.re.kr
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