235 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" uni jobs at University of Washington
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@MGI determines the functional impact of genetic variants (mutations) by engineering those variants into human cells. We use high content confocal microscopy and deep neural networks (machine learning
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statistical and machine learning methodologies to analyze and predict aspects of the collected data With the guidance of Drs. Stuber and Bruchas, develop experimental methodologies related to two-photon imaging
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. Demonstrate positive leadership skills such as empathy, creativity and fairness. Regularly assign, instruct and check the work of staff and students. Establish priorities in daily work to be done in section
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. Work Experience: No additional work experience unless stated elsewhere in the job posting. Skills: Accounting Processes, Adobe Acrobat, Analytical Thinking, Computerized Accounting, Computer Literacy
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experience in Machine Learning/Computer Vision/software engineering. Equivalent education and/or experience may substitute for minimum qualifications except when there are legal requirements, such as a license
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deadlines and policies. Data and Systems Management Serves as the Learning Management System (Canvas) administrator for the School. Enters and maintains accurate course scheduling information in
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of the physicians practice plans, see the link for additional benefits that may be available. For UWP: https://faculty.uwmedicine.org/wp-content/uploads/2019/09/UWP-Benefits-Summary-for-recruitingef-edits-v3.pdf
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acoustics. • Experience in End-to-End AI/ML production systems from inception to deployment. • Experience in one or more areas such as machine learning, pattern recognition, data mining, and
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with prescription access post-discharge Collaborate with inpatient/outpatient teams and PES staff to develop individualized transition plans Teach independent living skills such as budgeting, meal prep
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knowledge in immunology and proficiency in R and python. It would also be beneficial to have experience in high-performance computing environments, machine learning, git, whole-genome and exome sequencing