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intelligent decisions across society, advancing machine learning techniques, from foundations to industrial and scientific applications. About the research project You will work in Julian Togelius' new research
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chain, ranging from synthesis, cell assembly, characterization, modeling to scaled-up manufacturing. The 2-year postdoctoral project Machine Learning-based Electro-Chemo-Mechanical Estimation and Control
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methods that combine soundscape targets, acoustic metamaterials, physical modelling, inverse design, machine learning and perceptual evaluation. The postdoc will develop models and design methods
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of engagement. Read more at: Department of Computing Science Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven
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are looking for a Research Assistant in Machine Learning and Multimodal Digital Biomarkers with a focus on voice biomarkers, wearable sensing technologies, and performance monitoring, at the Department
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Do you want to contribute to the future of AI-driven electric transport systems? Join our research group to develop advanced machine learning methods for electromobility, focusing on energy-aware
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spans computational materials design, catalysis, energy materials, machine learning, and artificial intelligence. We offer a collaborative and international research environment with close interactions
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Documented ability to work in Python Experience with machine-learning methods for record linkage and text analysis Documented experience with machine-learning methods for image-to-text transcription
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data and multimodal datasets combining imaging and molecular measurements. Have a background in computational biology, bioinformatics, or machine learning for biological problems. Have experience with
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understanding: detection of objects and relations between objects, and use of these relations to infer new knowledge (i.e. reasoning); (ii) explore object affordances, learn the consequences of the actions