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Physics Informed Machine Learning method which exploits the advantages of physics-based and data-driven models, while mitigating the disadvantages. This research will contain experimental and modelling
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scientific leaders and researchers. The group of Wang Zhongjian is looking for postdocs working on scientific computing and machine learning related topics. The funding is currently under a MOE grant entitled
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on futuristic technologies in the field of machine learning and computer vision. Hence, we investigate and develop an innovative computation-in-memory (CIM) solution for artificial intelligence accelerator design
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
students, and collaborate with AI faculty in vision, robotics, and machine learning across the department. Minimum Education and Experience Requirements Applicants should have, or expect to receive before
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dynamics simulations and machine learning methods to study the structure and electrochemistry of disordered materials are also encouraged to apply. The project primarily aims to understand the complex
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CeMM - Research Center for Molecular Medicine of the Austrian Academy of Sciences | Austria | 2 months ago
International Postdoc Program - PreERC Postdoc Program (m/f/d) CeMM - Research Center for Molecular Medicine of the Austrian Academy of Sciences Vienna, Austria € 5,014.30 per month gross We are recruiting a
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Background in machine learning or deep learning methods, including Graph Neural Network (GNN) Experience with Large Language Models (LLMs) applied to biological data collection, extraction, and standardization
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experimental systems, from cell lines to primary neurons to ex vivo brain tissue. The postdoc will be encouraged to develop a unique scientific identity within the broader project, lead publications, present
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designing and building visualization dashboards. Research experience in human-centered AI, or in the integration of AI and machine learning methods into interactive visualization and analysis systems. Strong
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biomedical sciences. We are looking for candidates with A PhD in machine learning, computer science, computational biology, or a closely related field (completed or near completion). Demonstrated experience in