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Employee Patient Sensitive Job Code? No Standard Hours per Week 40 Full Time or Part Time? Full Time Shift Day Work Schedule Summary Monday through Friday. Exact schedule is to be arranged with supervisor
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Employee Patient Sensitive Job Code? No Standard Hours per Week 40 Full Time or Part Time? Full Time Shift Day Work Schedule Summary Monday through Friday. Exact schedule is to be arranged with supervisor
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, information, and biomedical visualization; image and data analysis; and interdisciplinary scientific computing and computational science. The Kahlert School of Computing is a highly collaborative and collegial
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, spectrophotometric assays, drug binding assays) Ion channel biology/electrophysiology Novel computational approaches (imaging analysis, protein design, etc.) If projects involve mouse models, then help supervise
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Required Skills: Current or planned MS or PhD student at the University in CS or related field. Solid background and working knowledge of computer science fundamentals including algorithms, data structures
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process. This position is not responsible for providing care to patients. This position is eligible for work from home and/or hybrid work options. Might be required to work onsite during training period
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involves the evaluation of digital images on a computer screen and identifies/characterizes ophthalmic features and pathologies in support of medical research activities. The tasks also include preparation
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Code Computer Employee Patient Sensitive Job Code? No Standard Hours per Week 40 Full Time or Part Time? Full Time Shift Day Work Schedule Summary VP Area Academic Affairs Department 00810 - Scient Comp
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Code Computer Employee Patient Sensitive Job Code? No Standard Hours per Week 40 Full Time or Part Time? Full Time Shift Day Work Schedule Summary VP Area Academic Affairs Department 00810 - Scient Comp
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computational and data science, with leading research and training programs in the areas of visualization, scientific and biomedical computing, and image analysis applied to a broad range of challenging problems