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Field
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place technologies and to develop digital twin algorithms to assist clinicians in developing treatment plans for patients with chronic diseases. Analyzes complex sensor data, works with a
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High-Energy Physics (HEP). We seek highly qualified candidates with interest and experience in ML algorithms including unsupervised techniques, time-series modeling, and clustering algorithms
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Integration: Integrate multi-modal data (e.g., single-cell RNA sequencing, spatial omics) to uncover new insights into cancer biology and therapy. Algorithm Development: Create and refine algorithms
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research associate position in AI for science. The Learning Systems Group seeks a postdoctoral researcher specializing in federated learning and privacy-preservation algorithms. The successful candidate will
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industrial imaging data. You will directly contribute to developing and deploying algorithms for multi-modal tomography (X-ray, neutron, and electron), advancing methods for non-destructive evaluation (NDE
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Imaging Sciences at the University of Arizona in Tucson, AZ is seeking candidates for an open Postdoctoral Research Associate position to train/work under the direction of Drs. Srinivasan Vedantham and Hsin
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machine learning, statistics, or applied mathematics that could drive the frontier of biomedical research. The role will be focused on the development of novel computational and algorithmic methods, with a
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, Weight, and Power) DAS system. - Develop calibration and processing pipelines for stable, low-noise operation. - Plan and run environmental tests (thermal/vacuum, vibration) and analogue field trials
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members Participate in traffic scenario generation project and pedestrian modeling project. Develop sophisticated AI-driven algorithms that create realistic, safety-critical test scenarios for autonomous
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optimization of optical imaging hardware, develop data acquisition software and algorithms for data processing, as well as perform phantom and human clinical studies. This candidate is expected to co-supervise