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algorithms to compute similarity between interaction interfaces across millions of comparisons. This hinders identification of novel modes of protein binding, i.e. those predicted by AlphaFold, and it hinders
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) and their effect on the sustainability of AI. This can be at the level of developing novel algorithms, training, learning and prompting paradigms, or hardware optimization techniques that can result in
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influence helps detect labeling errors or prioritize unlabeled images, optimizing the learning algorithm and service quality. The doctoral student will carry out their work at IMAG (UMR of Mathematics) and
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internationally. Main Responsibilities · Contribute to the installation, calibration, and validation of radio monitoring equipment. · Develop and test real-time data pipelines and deep learning algorithms for Solar
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Your Job: The conventional, manual co-design of algorithms and hardware is slow and inefficient. Our group develops methods and tools to automate the co-design process. The core of this project is
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ERC project FoRECAST, we aim to develop theory (e.g., new probabilistic and differential inference algorithms as well as proofs of their correctness and efficiency) and systems (e.g., high performance
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developing intelligent algorithms that can support repair and remanufacturing decisions for sustainable manufacturing? As a PhD researcher, you will create innovative machine learning solutions to optimize
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This project develops quantum-AI tools to optimise urban hydroponic food systems and evaluate their therapeutic impact on student well-being. The expected outcome is to create quantum-reinforced AI
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millions of US Dollars. Ensuring that contracts cannot be exploited is critical. The goal is to develop a language-agnostic verification approach, following on promising results related to the Solidity
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oriented towards the development of a domain-specific design automation framework for cryptographic hardware. Your work will focus on identifying the mathematical knowledge and properties to guide hardware