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. Have relevant research/industry experience in Machine Learning, AI and Privacy. An excellent team player who can cope with an agile and fast-paced environment. Good communication and interpersonal skills
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software testing and Machine Learning components. This research will have real-world impact through close collaboration with industry partner and offers the opportunity to contribute to cutting-edge
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from sensors or other continuous data sources. Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages
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research, oncology microbiomes, or environmental resistome surveillance. Familiarity with spatial metagenomics, single-cell microbiome analysis, or multi-omics data integration. Knowledge of machine learning
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platform that utilizes deep learning to analyze images of bruises. Responsibilities: Responsible for developing components of the project platform or deep learning application; Supervises a team of graduate
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interested in applicants who use advanced quantitative methods, including computational modeling, machine learning, and/or analyzing structural and functional neuroimaging data. Specific activities may include
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and oral communication skills, including drafting of academic papers and grants High level computer skills with software skills such as Microsoft Office, SAS, SPSS If this sounds like you, we highly
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Radio Frequency (RF) Systems: Extensive knowledge on network management and control Software Defined Radio (SDR): Data Analysis and Processing Programming and Software Development AI/Machine Learning (AI
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themes are not covered, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML
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themes are not covered, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML