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cognitive support and corrective feedback. You will apply advanced algorithms for machine learning, multimodal biosignal processing, and human-state inference, working with shared-control strategies and
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learning research, possessing a combination of mathematical maturity and advanced engineering skills: Education: A PhD in Computer Science, Mathematics, Statistics, or Theoretical Physics at the time of
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structured, well-documented way that supports benchmarking, reproducibility, and reuse by others. Essential: Strong data analysis and machine learning skills and experience with PyTorch (or equivalent
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efficiency. The goal is original research for leading machine-learning, computer-vision and robotics venues. The successful candidate will be expected to conduct original, high-quality research
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which you will be automatically redirected to an external site after 5 seconds) Save job Click to add the job to your shortlist Send job Job Details Are you interested in using machine learning to
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Postdoc in first-principles modelling and machine-learned force fields for correlated disorder in...
Chemistry at the Institute of Materials Chemistry, TU Wien. The group develops and applies electronic-structure theory, machine-learning methods and predictive calculations of defects and transport properties
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be carried out in close collaboration with researchers in wireless communications, sensing, machine learning, and robotics, with the ambition of producing contributions relevant to leading venues in
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, machine-learning methods and predictive calculations of defects and transport properties. The position will also be integrated into the wider CENSEMAT research environment at Aarhus University, allowing
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topics: Development of deep learning models Mathematical foundations of machine learning Optimal deployment of AI systems The candidate is expected to hold a relevant MSc degree in Computer Science
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degree Programming skills (Python) and experience with common machine learning platforms Experience with deep learning, computer vision, medical image analysis or unsupervised learning is an advantage