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established AGATE Centre for Algorithmic Game Theory in Socioeconomics. Informal inquiries are welcome and may be sent to loebl@kam.mff.cuni.cz . Where to apply E-mail positions@kam.mff.cuni.cz Requirements
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. Qualifications Required Qualifications: Completed PhD in biomedical engineering, electrical engineering, physics, or a medical imaging related field. Experience with developing advanced pulse sequences
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of the extraction and beneficiation system. This work will require an understanding of mining processes, mathematical modeling of flows and extraction decisions, and the use of machine learning algorithms to predict
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, NeRFs, Diffusion Models, LLMs, etc. PhD and PostDoc Positions in Visual Computing & AI The Visual Computing & Artificial Intelligence Group at the Technical University of Munich is looking for highly
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. You will take the lead on applied physics, mechanics, manufacturing processes, and algorithm/coding development within the bioprinting domain. This position is part of a larger, EU-funded Horizon Europe
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training algorithms and AI architecture. Image reconstruction, segmentation, and classification. High performance computing for spatiotemporal data. Major Duties/Responsibilities: Develop foundation AI
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at Durham University. This is a unique opportunity to work at the forefront of hydrogen technologies and their integration to the energy systems. The successful candidate will hold a PhD degree (or
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 18 days ago
computationally intensive, relying on iterative time-marching algorithms to reconstruct heating environments. This limits their use in more advanced computational analyses, such as uncertainty quantification
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Models with Algorithmic Reasoning Tasks We are seeking a postdoctoral researcher to contribute to our lab’s mission of aligning machine learning (ML) models with algorithmic reasoning tasks. Our goal is to
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and analysis of mathematical methods for novel imaging techniques and foundations of machine learning. Within the project COMFORT (funded by BMFTR) we aim to develop new algorithms for the training