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Field
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: Nonexempt Work Schedule: Flexible Summary The intern will receive training on machine learning algorithms, implementing them, and fitting them on the datasets in our cluster computers. Overall, the position
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: Nonexempt Work Schedule: Flexible Summary The intern will receive training on machine learning algorithms, implementing them, and fitting them on the datasets in our cluster computers. Overall, the position
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) Algorithm efficiency, asymptotic notation, solutions to recurrence relations. Greedy algorithms for graphs, scheduling problems, and greedy heuristic methods. Divide and conquer algorithms for sorting and
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on the development of artificial intelligence/machine learning algorithms to integrate multiple sources of patient-derived data, such as optical coherence tomography (OCT), retinal fundus photography (RFP), electronic
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algorithms for image analysis to facilitate and optimize early disease screening, diagnosis, and treatment. Ideal candidates should possess a M.S. or PhD (or equivalent) in computer science, mathematics
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maintain algorithms for accurate detection, segmentation, and classification of cells and structures in biomedical microscopy images. This position will also work to align high dimensional (HD) images of
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comprehensive scheduling algorithms) and handle sensitive information with confidentiality. Ability to work independently on a wide variety of tasks – both simple and complex - with minimal supervision and
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other duties as assigned. Work Schedule 40 hours per week, worked between the time frame of Monday-Friday between the hours of 7:00 am and 7:00 pm. Flexibility is expected regarding schedules to meet
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of early pre-malignant development of ovarian carcinoma and development of early detection/screening tests/algorithms of ovarian cancer. Qualified candidates must have a Ph.D. degree in Biology, Cellular
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limitations or potential issues with datasets and data types that may impact performance from machine learning algorithms. Re-trains models as needed to address new challenges or novel goals. Aids investigators