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: Develop and apply evolutionary 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
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exam. Desired qualifications: Experience with data simulation, clustering algorithms, benchmarking, model selection and evaluation workflows is an advantage Language requirement: Good oral and written
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over the parameter space) without specifying a model nor a prior. Such methods can in principle be applied to machine learning algorithms in order to get uncertainty estimates for parameters governing
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, please see: http://www.mn.uio.no/ifi/english/research/groups/ltg/ The successful applicant will benefit from close collaboration across disciplines and access to diverse application areas through the joint
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advantage. Language requirement: Good oral and written communication skills in English English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements: https
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that integrate prediction and control algorithms, optimizing data transformations, offloading and distributed computing, and exploiting mechanisms such as network slicing and multi-access edge computing
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without a master’s degree have until June 30, 2026 to complete the final exam. Desired qualifications: Experience with data simulation, clustering algorithms, benchmarking, model selection and evaluation
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algorithms for parallel/distributed AI/ML Hardware-aware and resource-efficient partitioning for parallel/distributed AI/ML Optimization of process-to-process communication in parallel/distributed AI/ML
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limits and human perceptual tolerances. The work will comprise designing networking and computing architectures that integrate prediction and control algorithms, optimizing data transformations, offloading
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Voytek at the Halıcıoğlu Data Science Institute (University of California San Diego, USA). By bridging experimental neurophysiology with advanced algorithmic design, we aim to significantly enhance