48 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" Fellowship research jobs at University of Michigan in United States
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, child care information resources, and access to dependent coverage for health insurance. For more details of benefits, please go to https://hr.umich.edu/working-u-m/my-employment/academic-human-resources
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references.. The Michigan Neuroscience Institute is an inclusive workplace that encourages individuals from diverse backgrounds and with diverse experiences to apply. Please visit: https://medicine.umich.edu
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at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work
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. Please visit the lab webpage https://sites.google.com/umich.edu/limbachlab Who We Are Vision: We aspire to be the world's preeminent college of engineering serving the common good. Mission: Michigan
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; treat others with respect, and dignity, and in a manner where individuals feel they belong; listen; value feedback; and learn from the perspectives of others. The stipend will be $70,000 per year based
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will have opportunities to take projects with them to their independent position. Lab website: https://sites.google.com/umich.edu/helmslab Mission Statement Michigan Medicine improves the health
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, machine learning and AI-based computational tools to advance biomedical as well as oncology research. The fellow will work under the supervision of Dr. Veera Baladandayuthapani and there will be
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. Experience working with medical images. Very good computer programming skills and physics background is essential. Desired Qualifications* Nuclear medicine imaging/dosimetry experience. Experience in image
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discipline or a related field - Strong demonstrated verbal and written communication skills Desired Qualifications* - Familiarity with manufacturing systems and processes - Experience with machine learning and
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of design and fabrication of medical devices, 3D printing, microfluidics, mechanics of materials, biomaterials, blood-material interactions, computer aided design, and/or in vitro/in vivo evaluation