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applications, including solving mathematical reasoning problems and tackling the Abstraction and Reasoning Corpus (ARC) challenge among others. The ideal candidate has a strong background in machine learning and
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Goldberg and will contribute to an ongoing EPSRC-funded project titled Optimisation for Game Theory and Machine Learning. The research associate will be based at Oxford and will work with Prof. Goldberg and
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Your profile PhD applicants must possess a Master's degree in mathematics, theoretical physics, or computer science. Candidates should have an exceptional academic record and a robust mathematical foundation. Candidates are also expected to have strong coding and implementation skills, with the...
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bioinformatics research coupled with wet-lab investigations, working in the areas of network biology, data-driven hierarchical modeling, and machine learning applied to biomedicine. We also support multiple open
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) level. This position is specifically focused on teaching courses in data-driven engineering, machine learning, dynamics, and control. This position is on a 9-month service period with an anticipated start
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enrollment: University of Ljubljana Duration: 36 months Supervisors: A. Žnidarič, A. Anžlin (ZAG), M. Skobir (CES) Objectives: Leverage vision-based monitoring and machine learning (ML) to enable enforcement
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for multimodal elastography and enabling deployment on portable devices (e.g., smartphones) for real-time diagnostics. The research combines continuum mechanics, machine learning, computational mathematics, and
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 1 month ago
with a team of engineers, snow scientists, and forest ecologists within the ESRC/EOS at the University of New Hampshire. The appropriate candidate will have cutting edge knowledge of machine learning and
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· Familiarity with applying machine learning techniques and concepts within practical implementations in healthcare domains preferred · Experience with ML frameworks and libraries such as TensorFlow
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Robotisation (PROMAR) group, headed by Matthias Rupp. The group develops fundamental and technological expertise in machine learning for materials science, including data-driven accelerated simulations and