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framework for understanding emergent deception in human-AI interaction by uniting behavioural-psychological, economic-strategic, and machine learning perspectives. The postdoc will be jointly supervised by
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, computer science, or engineering within the past 5 years. Previous theoretical and/or computational research experience in tensor networks, Monte Carlo, machine learning or a related field Proficiency in quantum
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Biology is desirable. Experience in the application and development of computational methods/tools or machine learning algorithms. Good computer programming skills in R/Matlab/PerlPython. Baylor College
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, solvent-based recycling process for complex plastic waste streams such as multilayer packaging and e-waste, while Exergy will develop the digital-twin and machine-learning tools that make the process
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packaging and e-waste, while Exergy will develop the digital-twin and machine-learning tools that make the process adaptive and scalable. The research effort will be directed towards the selective recovery in
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learning and deep learning. Specific Requirements PhD in acoustics. Knowledge of acoustical measurement techniques, as well as physical acoustics. Some experience in acoustic signal processing and machine
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for the analysis and integration of –omics data. The group has a strong track record in (integrative) computational omics analysis, algorithm development, machine learning and scientific data infrastructure
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 4 hours ago
migration in porous media under in situ conditions, and • Machine learning application to gas hydrate system to develop efficient key parameter estimation tools and large-scale 3D geologic model for gas
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for a short-term 2.5-month postdoctoral position (full-time) focused on developing and validating machine learning models that predict soil health and crop performance. The position will exploit datasets
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We are seeking a postdoctoral researcher with a curiosity-driven record who works at the intersection of machine learning (ML) and the sounds of wildlife (“bioacoustics”). We are also happy