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of the state of the art in Evolutionary Algorithms and Large Language Models. Survey of the state of the art in Evolutionary Algorithms applied to Large Language Models. Implementation of an evolutionary
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to the development and implementation of approaches that interface with living systems through novel materials and algorithms, electric and magnetic fields, ultrasound, optics and targeted radiation, microfluidics
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algorithms, capable of distributed learning on high performance and edge computing; The design of architectures/models which accurately capture the complexities of the data, with robust estimates of confidence
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extension to four years, will focus on leveraging the next generation of evolutionary algorithms to evolve efficient, robust, and interpretable predictors and data processing algorithms. A crucial aspect will
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research unit attached to the CNRS, the University of Bordeaux and the Ministry of Culture. Its research focuses on the evolutionary, cultural and symbolic history of past populations in relation
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high-dimensional, dynamic, networked system, applying techniques from machine learning, causal inference, statistics, and algorithms. No prior biomedical training is required—just strong quantitative
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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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biology and bioinformatics, as well as in Machine Learning (including Large Language Models). Good understanding of evolutionary and molecular biology concepts, and good statistical (data analysis) and
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development and application of novel algorithms and machine learning/AI techniques for extracting insights from biological data sets (genomics, proteomics, imaging, neuroscience), and related areas
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circuit design, the development and application of novel algorithms and machine learning/AI techniques for extracting insights from biological data sets (genomics, proteomics, imaging, neuroscience), and