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research themes include Affective Science; Neuroscience; Personality and Individual Differences. To learn more please visit our site at https://artsci.tamu.edu/psychological-brain-sciences/index.html We
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/Office/Project; SAP; KRONOS Minimum of five (5) years related facilities healthcare maintenance including knowledge of machines and tools, their designs, uses, and repair — Preferred Knowledge of building
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knowledge, incorporate reliability/uncertainty, and/or explainable models. The position is in the Digital Signal Processing and Image Analysis Group, Section for Machine Learning, Department of Informatics
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University of California, San Francisco | San Francisco, California | United States | about 8 hours ago
relevant experience Knowledge of safe and therapeutic care for mothers and newborns; or a willingness to be taught/learn new skills Ability to work effectively within a team Ability to satisfactorily perform
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understanding of how clinical data science and machine learning impact healthcare data in addition to guidance on programming methods to process data. Basic programming skills (Python or R) and knowledge
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to the student and administrative/faculty members as appropriate. Other duties as assigned by the program administrator. Basic knowledge of technology-mediated platforms for blended learning and computer software
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architecture, concurrent systems, cryptography, databases, distributed systems, game theory, graphs, knowledge representation, logic, machine learning, networks, operating systems, programming languages
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performance data using recommended guidelines and machine learning tools Defining the uncertainty sources Enhancing existing guidelines for full-scale power-speed assessment practice Disseminating research
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technical contributions as an embedded software engineer for a wide range of projects requiring computing systems design and realization, including machine learning (ML) and artificial intelligence (AI
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-omics liquid biopsy data for minimal residual disease (MRD) detection, quantification, and assessment. This project will involve applying and evaluating statistical and machine learning models for data