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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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, interventional effects, multiple mediation), and advanced longitudinal modelling (mixed-effects models, growth curve models, latent class trajectories) with machine learning and AI-based approaches. The Lab is
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qualification; (ii) demonstrate research skills in imaging science and machine learning, particularly on image reverse engineering, fake image and video detection, statistical detection models and mathematical
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/index.html The researcher will be part of a growing team of researchers, postdocs and PhD students working on intelligent observing systems using machine learning and data assimilation methods in the ACTIVATE
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will work across the following research areas: Predictive machine learning Robust and stochastic optimization Learning-enabled control and reinforcement learning Power system operations, planning, and
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community partners to ensure outputs reflect local priorities and inform adaptation planning. Duties may include: Develop spatially explicit computational models using machine learning, hydrologic, and energy
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systems to rapidly traverse evolutionary landscapes Evolution of complex, multi-gene phenotypes Engineering plug-and-play selection systems for continuous evolution of diverse phenotypes Learn more at How
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broad implications for how we understand and engineer life. Learn more at How to apply Applications will be reviewed on a rolling basis. In your cover letter, please clearly explain your fit, interest
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for remote sensing and uncertainty estimation. Candidates must have a strong programming background. Requirements: PhD in Computer Science or a related field with a strong emphasis on machine learning
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needed, and otherwise contribute to overall lab operations. The applicant will be a collaborative, impact-focused problem solver who wants to be part of a dynamic team. Learn more about the innovative work