86 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at University of Minnesota
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applications. Presenting and Instruction - 10% • Present research summary in national and international meetings in oral and poster format by preparing abstracts and slides for presentation. • Instruct students
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. Prepare result summaries to share with collaborators Qualifications Required Qualifications: PhD in Animal / Biological Science or related field Prior experience in cell culture, cellular and molecular
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this position you may also have the opportunity to teach courses offered in our department. These duties would be to prepare and deliver lectures, prepare homework assignments, quizzes and exams, hold office
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students on data analysis and detector projects. 40% Instruction of introductory physics lecture section 25% Core reconstruction and simulation software and computing development 15% Construction
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(DVM, PhD, or equivalent) degree(s) by start date and should be able to demonstrate experience on pathogenesis, epidemiology, or virology of veterinary pathogens. Candidates with a strong background in
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environment and appreciation of differences in the workplace The selected candidate must have, or be able to acquire, Special Sworn Status, to work in the Federal Statistical Research Data Center (FSRDC), of
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skills or allows them opportunities to learn new research techniques. They are trained and work in conjunction with a faculty mentor who determines the training agenda. Post-Doctoral Associates may
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Please visit the Benefits for Postdoctoral Candidates website for more information regarding benefit eligibility. Competitive wages, paid holidays, and generous time off Continuous learning opportunities
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motor learning is available immediately in the laboratory of Dr. Aaron Kerlin (www.kerlinlab.org). Successful applicants will use state-of-the-art equipment we have constructed for the in vivo measurement
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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