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Stanford University is seeking a Software Developer 1 to join the Kundaje lab in the Department of Genetics to lead and assist with large-scale software development efforts at the interface of machine
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advanced retrieval techniques, including spatio-temporal regularization, and hybrid methods with machine learning and deep learning. He/she will support the development of an improved forest RTM that can
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Summary Assist with online classrooms at graduate and/or undergraduate levels in the Instructional Design & Technology program and/or the Management & Technology major. May participate in
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AI systems Applicants should have (i) a Ph.D. degree in Computer Science, Computer Engineering, Electrical Engineering, or a closely related discipline; (ii) a strong research track record demonstrated
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(target journals: International Journal for Numerical Methods in Engineering – IJNME). Deep learning algorithms for high-temperature multiphase problems (target journals: Computer Methods in Applied
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: “Towards a trustworthy strategic use of data in machine learning pipelines”. CUP: D53C25002380001. Where to apply Website https://aunicalogin.polimi.it/aunicalogin/getservizio.xml?id_servizio=1079
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at the interface of biostatistics, machine learning, and biomedical data science. This mentored postdoctoral position is designed to support the development of an independent research trajectory in methodological
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researchers with expertise in computational biology and machine learning/AI for synthetic biology applications to join our group at National University of Singapore for the engineering of microbes as biosensors
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relational database environments Apply and evaluate methods from causal inference (e.g., confounding control, bias assessment, sensitivity analyses) Apply machine learning approaches for predictive modeling
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course development, including student learning outcomes and assessment processes Participate in the development and/or selection of course materials, equipment, and technology that will enhance