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Field
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projects. With greater autonomy, you will design experiments, interpret data, and collaborate with senior researchers to develop and refine research protocols. Your role may also include mentoring junior
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systems, Wireless Power transfer, Thermal/colling management, and Battery Management Systems. • Develop digital twins of the detailed electrical power system based on the concept design in real-time
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setups and develop methods for in-situ diagnostic and monitoring additive manufacturing (AM) processes toward the 3D printing of metal alloys and ceramics. The successful candidate will use optical and
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opportunity to develop cutting-edge AI-enhanced algorithms for analyzing transposable elements (TEs) in cancer epigenomics, with direct translational applications to precision oncology and immunotherapy
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 2 months ago
. Lab Research: • AI-Driven Algorithms & Software: Develop deep leering/machine learning/statistical based algorithms to elucidate lncRNAs, fusion transcripts, RNA modifications, and circular RNAs in
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designing DNA, RNA and proteins to create nanoscale devices for applications in biotechnology and medicine. The lab invented the RNA origami method [1] and have developed basic algorithms and software for RNA
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medicine. The lab invented the RNA origami method [1] and have developed basic algorithms and software for RNA design. However, there is a great need to develop new software for the design of advanced RNA
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medicine. The lab invented the RNA origami method [1] and have developed basic algorithms and software for RNA design. However, there is a great need to develop new software for the design of advanced RNA
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diseases and their impact on interstate and international trade and community health. They will learn surveillance procedures, diagnostic testing methodologies and algorithms, serological diagnostic methods
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for characterization of CT images. Machine and Deep learning: Develop and implement machine learning and deep learning algorithms to built detection and prediction models for CT images Performance Evaluation: Conduct