85 phd-computer-artificial-machine-human Postdoctoral positions at University of Minnesota
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Qualifications Essential Qualifications • PhD in mathematics, science or STEM education research or equivalent (e.g., PhD in biological field with dissertation on discipline-based education research) • Experience
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, working groups Qualifications Required Qualifications: ● PhD in water resources, hydrology, aquatic ecology, limnology, wetland ecology or a related field ● Experience with synthesis and analysis of large
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. Expected distribution of duties includes: ● Laboratory benchwork: 75% ● Data analysis, writing, and presentations: 25% Qualifications Required Qualifications: ● A PhD degree in Neuroscience or a related
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%). • Contribute to data and lab management (5%) Qualifications Required Qualifications: • PhD, DO, MD or similar degree in health sciences or related field • 3+ years experience in biological sciences laboratory
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to lead a project related to the transport of bacteria in porous media and multiphase flow. A PhD degree in engineering or earth science is needed. 75% - Conduct laboratory experiments related
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hydrology and computer science. Any previous success in leading and delivering academic deliverables of using machine learning in solving hydrological problems and experience in spurring interdisciplinary
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(subfield: experimental condensed matter physics) or closely related field, such as Electrical Engineering. Preferred Requirements: Applicants whose PhD work included substantial experimental work with a
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in the lab and is expected to foster the development of junior lab members. Qualifications Required Qualifications: The ideal candidate will have a PhD in microbiology, biochemistry, bioinformatics
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Regular/Temporary Regular Job Code 9546 Employee Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job Qualifications Required: PhD in physics, chemistry, biophysics, biochemistry
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technologies and how their technology use impacts their relationships and well-being, and on the application of machine learning in family and developmental research. The Post-Doc will contribute to Dr. Sun’s