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Institute of Systems and Robotics, Faculty of Sciences and Technology of the University of Coimbra | Portugal | 21 days ago
Engineering Research Field Engineering » Electrical engineering Engineering » Electronic engineering Engineering » Mechanical engineering Engineering » Computer engineering Researcher Profile First Stage
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, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and grow'. We welcome you to join our community
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projects on metabolic diseases * Develop and apply machine learning models for biomarker discovery, patient stratification, and prediction of disease trajectories * Collaborate with clinicians
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integration Key areas: § Metagenomic and 16S rRNA sequencing analysis § Single-cell RNA-seq and proteomic/metabolomic data integration § Machine learning and AI applications in microbiome data
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learning to model solid-state materials while collaborating with experimentalists. Qualifications • Ph.D. in Computational Physics/Materials Science, or related field (completed by start date
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 24 days ago
deep learning theory and practice. Applicants with expertise in probabilistic modelling, approximate inference, deep learning, or Bayesian optimisation are encouraged to apply. Interpretable Machine
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), one method of SCI, poses on the Earth system. Specifically, the postdoctoral scholar will analyze climate model simulations to quantify the impacts and risks of SAI on climate extremes such as droughts
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machine learning models with respect to accuracy and uncertainty quantification. - Developing software to implement the goals stated above (most likely in Python). - Disseminating results
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journals. Internal knowledge transfer, and collaborative research efforts. Develop and evaluate AI models, including, but not limited to, those for Multi-Agent Systems, Multi-Agent Reinforcement Learning
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The lab of professor Jesper Tegnér at KAUST has openings for three postdoctoral fellowships in Data-driven Machine Learning for unbiased Discovery of Generative Models with special reference