72 phd-in-computer-vision-and-machine-learning Postdoctoral positions at University of Minnesota
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on the development of Bayesian statistical/machine learning methods for the data integration analysis of high-throughput imaging and molecular data (i.e., genome, transcriptome, epigenome, and more). The methods would
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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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on application materials. Required Qualifications: • PhD in Immunology, Cell Biology, or related biomedical sciences • In-depth scientific expertise in cell death, macrophage biology, and fibrotic disease
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on application materials. Required Qualifications: • PhD in Immunology, Molecular Biology, or a closely related biomedical field • Strong foundation in cellular and molecular immunology, with demonstrated
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. The candidate must have a track record of reliability and good verbal and written communication skills. This is an ideal position for a recent graduate with an PhD, MD/PhD degree in related fields, but not
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with other faculty and collaborators, including, if required traveling to international destinations to meet with collaborators and collect data (10%). Qualifications Required Qualifications: PhD in
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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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, implement, and evaluate computational models that assimilate 2-photon data (60%) Use a computer programming language to create novel neural network simulations (models) that include realistic simulations
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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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) Qualifications Essential Qualifications PhD in forestry or closely related field such as land resources Preferred Qualifications Have experience with bark beetles, tree defenses, and climate data Have experience