119 algorithm-sensor-"University-of-California" Fellowship positions in United States
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fellowship in Pathology and Clinical Informatics (CI) at the University of California, Los Angeles. The program is open to pathologists only. Please visit our website: https://www.uclahealth.org/departments
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | 33 minutes ago
software tools in order to develop biometric algorithms for recognition, spoof detection, fairness in AI, template security, and explainability, and related research areas, as well as paper and report
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Medicine and Bioinformatics. The specific objectives of the project are to (i) deploy network analysis methods to genomic data (50%), and (ii) develop such algorithms including community detection algorithms
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the University of California Policy on Vaccination Programs , as may be amended or revised from time to time. Federal, state, or local public health directives may impose additional requirements. The University
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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objectives of the project are to (i) deploy network analysis methods to genomic data (50%), and (ii) develop such algorithms including community detection algorithms (50%). PhD in computer science, engineering
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at intersections through real-time detection, classification, and tracking of vulnerable road users (VRUs) using advanced sensing technologies and artificial intelligence algorithms. The appointment is tentatively
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science, with a particular focus on neuroscience applications. Designs AI techniques and algorithms for multimodal data fusion (e.g., MRI, EEG, cognitive and behavioral data, blood biomarkers, and
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sensors or inductive sensors, and demonstrate temperature readout of magnetic nano-objects engineered with high thermosensitivity. For the past 6 years, our team has been developing instrumentation
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apply cutting-edge machine learning algorithms, with focus on foundation models and LLMs/agents, to analyze complex biological data. This data includes gsingle cell genomics profiles, spatial data, and