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academic institutions to translate research into viable solutions. Job Requirements: Preferably PhD in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly
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research, analysing user and learning data, and producing academic and grant-related outputs. Requirements: Essential PhD in Education, Learning Sciences, Educational Technology, Human-Computer Interaction
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framework or knowledge graphs; 2) Uncertainty analysis and risk modelling; 3) Port and maritime operations; 4) Cybersecurity or critical infrastructure protection; and 5) Machine learning and real-time data
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excellence. Assisting in the mentorship of junior analytical staff members and graduate students QUALIFICATIONS A PhD in computational biology, bioinformatics, statistics, computer science (Machine Learning
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wide range of backgrounds and experiences. You should demonstrate: Essential Criteria Relevant academic training and a PhD (or equivalent experience) in a relevant subject such as health economics
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, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with causal machine learning, ensemble methods, and deep learning
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Oden Institute for Computational Engineering and Sciences | Austin, Texas | United States | 2 months ago
genetic data Multimodal machine learning for biological discovery Translational genomics and risk modeling The fellow will work in an environment that emphasizes methodological innovation, statistical rigor
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insurance, supported by INESC TEC. 2. OBJECTIVES: • Explore machine learning approaches for discovering interpretable and clinically relevant visual representations.; • Validate the proposed methodologies
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, including parsing and processing large document corpora. Strong understanding of machine learning or AI methods applied to health or biomedical data. Demonstrated ability to assess model outputs, identify
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We are seeking a Research Fellow - Data Science professional with strong expertise in machine learning, deep learning and high-frequency physiological signal analysis. This is a unique opportunity to