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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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the Sterne-Weiler Lab i n Computational Biology / Discovery Oncology. The postdoctoral position is focused on developing and applying foundational AI models to investigate clinically relevant cancer
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 10 hours ago
Summary About the Group: Our research group is dedicated to developing innovative datasets and modeling approaches to support drug development and regulatory evaluation. We focus on two major research areas
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of performance, speed, and precision. Key Responsibilities: Design and implement genAI models for embodied AI systems. Develop and optimize deep learning algorithms to enable robotic arms to perform complex tasks
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your career in one of the world leading research institutions in Transport? Based in the Institute for Transport Studies at the University of Leeds, you will primarily contribute to the modelling and
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the opportunity to work at the forefront of cardio-oncology science, combining sophisticated small animal radiation models, single-cell transcriptomics and state-of-the-art echocardiography. The successful
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/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: The overall vision of the ATE is to deploy and demonstrate a set of business models
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, attention-based models, and multi-modal learning approaches—to model RNA-mediated regulatory mechanisms and their dynamic interactions in disease. The position is part of an NHMRC Ideas Grant project
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Models – information to be provided in the CV. Additional optional skills and qualifications: Preference will be given to candidates with previous experience in the areas of biochemistry and data analysis
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candidates for a Postdoctoral position. This position is available to individuals with research interests and expertise in modeling and data analyses of hydrologic processes. The College and/or the Civil