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structure calculations, vibronic property simulations, and analyzing surface adsorption phenomena. Knowledge of machine learning potentials (e.g., GAP, ACE) or reactive force fields is a plus, as fallback
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://robotsinsociety.blogs.dsv.su.se/ ) is to advance the critical interactional study and design of autonomous systems and robotics in society. This postdoc will join this research group to develop interaction design research
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Responsibilities We are looking for a highly motivated Postdoc in the areas of Probabilistic Machine Learning and Neuro-Symbolic AI to contribute to the Cluster of Excellence “Bilateral AI (BilAI),” funded by
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programming and instrument control using Matlab, Python, Labview etc Machine / deep learning expertise Strong analytical skills and ability to work in a multidisciplinary team Excellent communication and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
our group at the intersection of statistical methodology, machine learning, and biomedical data science. Our research develops rigorous and interpretable methods for high-dimensional biomedical data
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enterprises (SMEs). The postdoc will work at the intersection of cybersecurity, machine learning, and human centered system design, contributing to the research on privacy aware monitoring, attacker modelling
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to leverage machine learning approaches for the optimization of polymer properties and degradation profiles. The successful candidate will lead pioneering research in controlled polymer synthesis, employing
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coarse grained reconfigurable arrays (CGRAs), virtualisation of FPGAs using partial reconfiguration, and accelerator support for machine learning. Postdocs at KAUST enjoy generous salaries and free
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machine learning methods for detecting, classifying, and identifying wireless anomalies in real-world radio environments. You will design and experiment with AI-driven approaches for spectrum analysis, work
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for 3 years. The project is conducted in close collaboration with the SFF Integreat, The Norwegian Centre for Knowledge-driven Machine Learning (ML) , a centre of excellence funded by RCN and in operation