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Associate with background on AI and machine learning for wireless networking and communications. The successful candidate will work under the direction of Dr. Marwan Krunz, Director of the Wireless
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the ability to quickly learn new things and work independently, along with previous research experience in at least one of the following areas: 1) statistical genetics/genomics/omics, or 2) deep/machine
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, proteomics, metabolomics) and artificial intelligence/machine learning (AI/ML) applications in biomedical research will be considered a strong advantage. Outstanding U of A benefits include health, dental
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, registry data, health data, laboratory data, electronic health records, biomedical informatics standards. Working kowledge or direct experience in SCN8A-related disorders. Experience in machine learning
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status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu Employment Requirements Any offer of employment is contingent upon
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nuclear physics detectors. Experience analyzing data from high energy or nuclear physics experiments. Familiarity with Monte Carlo simulations. Familiarity with machine learning techniques. About the
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machine learning methods. Provide theoretical predictions to guide experiments, and atomic-scale physical understanding to experimental observations. Publishing findings in peer-reviewed journals
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Experience with super-resolution ultrasound, US localization microscopy, photoacoustic imaging, elasticity imaging, pulse encoding, solving inverse problems, machine learning, AI, SolidWorks, 3D printing FLSA
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the application of machine learning techniques (e.g., doc2vec, encoder models, multi-modal embeddings, large language models) to map concepts and their relationships, tracing how they change, merge, or diverge
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machine learning analyses will be performed to determine correlations across stimulation settings and body systems as well as to develop predictive models and biomarkers for physiological and clinical