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. Research opportunities will focus on the use of novel modeling tools for hydrology and water resources systems, with an emphasis on machine learning and remote sensing, with a focus on developing detailed
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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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available single-cell sequencing data generated from patient samples and mouse models, we will enhance and apply machine-learning based algorithms to deconvolute bulk tumor RNA-seq samples to distinct immune
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projects utilizing machine learning, deep learning, and generative AI to solve business and healthcare problems have been undertaken at the Insight Lab. For more details, please refer to: https
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neurocritical care research The Opportunity We are seeking a Research Fellow - Data Science professional with strong expertise in machine learning, deep learning and high-frequency physiological signal analysis
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health records (EHR), waveforms from bedside monitors, radiology images and wearable sensors. This position offers a unique opportunity to work closely with clinicians on applications of machine learning
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embedded AI systems. They will demonstrate a strong track record of high-quality research in machine learning/AI and/or embedded systems, evidenced by publications in leading conferences and journals
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requirements: PhD degree in Computer Science, Electrical and Electronic Engineering, or related field. At least 3 years of relevant experience in computer vision, artificial intelligence, etc. Proficiency in
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a focus in economics, or related disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation
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., • Interest in developing risk prediction models via deep learning/machine learning. • Have strong background in DL, EEG data and programming for the implementation of proposed methods. Apply now