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Responsibilities We are looking for a highly motivated Postdoc in the areas of Probabilistic Machine Learning and Neuro-Symbolic AI to contribute to the Cluster of Excellence “Bilateral AI (BilAI),” funded by
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to leverage machine learning approaches for the optimization of polymer properties and degradation profiles. The successful candidate will lead pioneering research in controlled polymer synthesis, employing
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disciplines. Familiarity with contemporary AI systems (e.g., machine learning, generative models) at a conceptual or applied level. Experience with qualitative or mixed research methods (e.g., ethnography
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machine learning methods for detecting, classifying, and identifying wireless anomalies in real-world radio environments. You will design and experiment with AI-driven approaches for spectrum analysis, work
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neuroscience, and brain-computer interfaces, machine learning and deep learning, statistical modelling, regression methods, and uncertainty quantification, calibration, interlaboratory comparisons, and
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/scholarship during postdoc appointment period. Projects in the Birnbaum lab focus on plant regeneration and plant cell development. This postdoc will work on a new project on somatic embryogenesis in poplar and
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machine learning models directly on these edge devices for real-time anomaly detection and identification. You will develop robust signal acquisition and processing pipelines, translate research-grade
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skilled in object-oriented coding (preferably Python) and data analysis; affinity with machine learning and explainable AI techniques, preferably in a geoscience context; good social skills. As a university
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Vacancies PostDoc position on VR training for first responders dealing with “Personen met Onbegrepen Gedrag” (Dutch language) Key takeaways We offer a challenging PostDoc position with the Human
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about faculty research programs, network with Fred Hutch postdocs and faculty, and learn about the postdoctoral training environment and the vast resources available at Fred Hutch. This program is