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Field
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new generation of embedded intelligence within grid-connected power converters and variable-frequency motor drives with edge computing and machine learning capabilities. The Postdoc positions are part
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developing machine learning models - Genetic or molecular lab experience - Bioinformatics, or statistical genetics experience - Excellent written and oral communication skills Special Instructions
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models, causal inference and machine learning. Dr. Liu's research interests lie in modeling the rapidly-accumulating big data (e.g., muti-omics) in biology and medicine for precision medicine via a
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machine learning–based analysis. Behavioral features are compared at inter- and intra-disease levels to identify disease-specific signatures and establish a foundation for future circuit-level
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group with responsibility for carrying out research in rough path theory, machine learning, generative AI and related fields as part of the DataSig II grant “High order mathematical and computational
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Systems at The Technical Faculty of IT and Design invites applications for a PhD stipend in the field of secure machine learning within the general study programme Electronic and Electrical Engineering
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(e.g. sparse-view and/or high-noise) data. Develop and validate numerical implementations on simulated and real CT data. Explore and compare supervised and self-supervised machine learning/AI-based
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developing and evaluating learning-based approaches for controlling infectious disease spread under realistic epidemiological, operational, and societal constraints. The postdoc will work at the
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within a research team Record of peer-reviewed publications or manuscripts in preparation Preferred Qualifications Experience with machine learning and deep learning Ability to analyze and interpret
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within a research team Record of peer-reviewed publications or manuscripts in preparation Preferred Qualifications Experience with machine learning and deep learning Ability to analyze and interpret