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Field
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to the development and assessment of emerging technologies and AI. This post-doc position will involve responsibilities including: Supporting teaching and instructional innovation as part of new program development
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single-cell transcriptomic data. The candidate should be proficient in, or highly motivated to learn cancer data science, machine learning, and high throughput sequencing analysis. Successful applicants
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researchers in pursuit of advancing knowledge and making significant contributions to their respective fields. ESSENTIAL QUALIFICATIONS/EXPERIENCES PhD Graduation; Strong background in deep learning, machine
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, engaging with other data analysts, students, post- docs and faculty on the team Conduct comprehensive high-throughput multi-omics data analysis and epidemiological analyses; Apply biostatistics and cancer
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analysis of atmospheric numerical model output (e.g., WRF, PALM, SAM) Experience with machine learning and artificial intelligence techniques Experience with predictive modeling Environmental, Health
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studies. Proficiency in relevant computational tools and statistical methods. Experience with machine learning in large datasets. Interest and motivation to work in a multidisciplinary team. Ability to work
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Previous Job Job Title Post-Doctoral Associate Next Job Apply for Job Job ID 367495 Location Twin Cities Job Family Academic Full/Part Time Full-Time Regular/Temporary Regular Job Code 9546 Employee
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Previous Job Job Title Post-Doctoral Associate Next Job Apply for Job Job ID 367615 Location Twin Cities Job Family Academic Full/Part Time Full-Time Regular/Temporary Regular Job Code 9546 Employee
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) Advanced statistical evaluations (in particular machine learning-based analyses and research syntheses such as scoping/systematic reviews, meta-analyses and meta-science approaches) Leading functions in data
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, enhanced by machine-learning and data-driven analysis techniques. Additionally, the study will encompass electrically triggered events that mimic the voltage-based signaling of biological synapses