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Field
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well as machine learning and multivariate decoding of neuroimaging data to predict subjective experiences and individual differences. Successful candidates will be supported in building a research program at the
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Trustworthy AI Systems NSF Research Traineeship, the Digital Trade and Data Governance Hub, the Center for Machine Learning, and the Human-Computer Interaction Lab at UMD, and the Center for Equitable AI and
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, biophysics, applied mathematics, or related field. Expertise in machine learning, computer vision, or image analysis. Experience with data management and databases. Experience working with Python, scientific
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/communications, machine learning/vision, intelligent transportation systems, intelligent sensing/localization, or signal processing. In line with our Athena SWAN ambitions we especially encourage women to apply
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Paravision Micro-CT, optical imaging, photoacoustic imaging, PET, or SPECT Artificial intelligence or machine learning for biomedical image analysis Python, MATLAB, C++, or similar scientific programming
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autonomous, closed-loop (“self-driving”) laboratory workflows. The role integrates catalyst synthesis, high-throughput reactor testing, and in situ/operando characterization with machine-learning and agentic
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, and machine learning, the program prepares graduates to drive progress in fields like renewable energy, 5G, cyber-physical systems, and smart infrastructure. University Information The University
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, project management, and presentation skills Proficient with computer applications and programs associated with the position (i.e. Microsoft Office suite) Strong attention to detail and follow-up skills
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of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI implementation. Ability to apply AI to interdisciplinary research or developing AI models
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: Conceptualisation and synthesis of data integration and visualisation workflows. Data management and the development of knowledge graphs Development and application of AI and machine learning methods and pipelines