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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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, 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 the successful completion of a
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-doctoral Associate will develop algorithms and theory for machine learning methods, as well as implement and apply ML methods to problems in domains such as computational biology and neuroscience. This is a
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disease-causing organisms. Outstanding U of A benefits include health, dental, vision, and life insurance; paid vacation, sick leave, and holidays; U of A/ASU/NAU tuition reduction for the employee and
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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