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Diego, USA). By bridging experimental neurophysiology with advanced algorithmic design, we aim to significantly enhance the understanding of high-dimensional neural activity patterns. The successful
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to machine learning algorithms in order to get uncertainty estimates for parameters governing the distribution of the observed data. The predictive Bayes scheme for uncertainty quantification contains a wide
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for measurement challenges (e.g., for small-sample calibration or for accelerated algorithms), (b) identifying and investigating aberrant response behavior (such as rapid guessing, cheating, or careless responding
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will work on the following topics, in collaboration with the rest of the team: Develop and apply evolutionary algorithms to jointly optimize both the robot’s morphology and autonomy, and apply quality
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of Artificial Intelligence (AI), and therefore a fundamental force of technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories, methods, models and
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-based methods to achieve personalised and novel outputs. This position will have a particular focus on developing fundamental AI algorithms and methods that can be used in systems for real-time creative
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algorithms to jointly optimize both the robot’s morphology and autonomy, and apply quality-diversity methods to discover a wide range of high-performing designs. Work on genotype-to-phenotype mappings
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(AI), and therefore a fundamental force of technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories, methods, models and algorithms
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technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories, methods, models and algorithms that integrate general and domain-specific knowledge with data
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needs of the research center. More specifically, the postdoc will work on the following topics, in collaboration with the rest of the team: Develop and apply evolutionary algorithms to jointly optimize