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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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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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revealing mechanisms and therapeutic targets of early pre-malignant development of ovarian carcinoma, novel big data approaches, and development of early detection/screening tests/algorithms of ovarian cancer
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algorithms, creating software, and investigating new approaches and technologies. Assists with the development of conceptual project design and instrumentation, software programs, and data collection methods
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learning algorithms focused on image data, natural language processing, and tabular data Conduct exploratory data analysis and feature engineering for high-dimensional datasets, including image, text, and
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Python Proficiency: Demonstrate expertise in Python or a similar high-level programming language is essential for developing algorithms and backend logic Azure DevOps Experience: Familiarity with Azure
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materials, implementing algorithms, creating software, and investigating new approaches and technologies. Assists with conducting research, including setting up, calibrating, maintaining research records
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to create analytic data cohorts (study cohorts). Apply machine learning methods on clinical datasets to identify predictive factors – selecting algorithms, preprocessing data, training models, and evaluating
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methods development, novel algorithm development and/or in-depth data analysis that facilitates and integrates implementation, visualization, and database management of multi-dimensional clinical and
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statistical methods to mine and analyze complex and unstructured data sets. Offers complex analysis and utilizes advanced algorithms and statistical software. Adheres to all protocols. Essential Functions