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Field
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systems for accelerating computational catalysis and experimental design. The successful candidate will contribute to building AI-native frameworks that combine first-principles modeling, machine-learning
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on studying the principles of neural computation through recurrent neural networks, dynamical systems theory, and machine learning. - Develop mathematical and computational models of neural networks - Analyze
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Max Planck Institute for Radio Astronomy, Bonn | Bonn, Nordrhein Westfalen | Germany | about 2 hours ago
on the true, astrophysical candidates is a computational needle in a haystack. To tackle these “big data” challenges, astronomers have begun to employ machine learning techniques. The application of machine
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, machine learning and deep learning. The project Motivation: Interpreting the genome means modeling the relationship between genotype and phenotype, which is the fundamental goal of biology. Achieving
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of Engineering Science. The post is funded by EPSRC and is fixed term to the 31st January 2027. A2I explores core challenges in AI and machine learning to enable robots to robustly and effectively operate in complex, real
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frameworks for quantum machine learning, including conformal quantum prediction and uncertainty quantification in quantum models; Theoretical and algorithmic advances rooted in statistical learning theory
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are looking for a motivated postdoc with solid experience in bioinformatics and in machine learning. The position centers on SRPs and LLPS, and the successful candidate will contribute to several ongoing
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, and other methods. Collects data using cameras, sensors, and data acquisition systems. Prototypes, troubleshoots, and fine-tunes machine learning models for outcome predictions relevant to surgery
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motivated post-doctoral associate with a strong background in control systems and machine learning to join the research team of Prof. M. Umar B. Niazi. The position focuses on the development of digital twins
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Oxford Nanopore Technologies (ONT). Your role will be central in creating and applying bioinformatics and machine learning tools to analyze long-read data and decipher cap-specific signals from raw