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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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of Pittsburgh. This Lab examines the intersection of public health, epidemiology, and ophthalmology. The candidate should have a PhD in a statistics-related field and at least one year of experience in analyzing
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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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neuroprotection, we will use advanced single-cell and spatial transcriptomics techniques. Minimum experience: 5+ years in Ophthalmology research PhD in Biomedical Sciences or similar The University of Pittsburgh is
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education is not needed. Ability to solve problems, and to structure project plans to completion must be demonstrated through previous work experience. PhD in STEM field is required for this position
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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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positions that are commensurate with prior training and experience. Preference will be given to PhD or MD/PhD applicants with considerable experience studying the neural control of the pelvic organs
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on our first-year composition courses, visit http://composition.pitt.edu/undergraduate/first-year-composition . MA or higher degree required; terminal degree (MFA, PhD, etc.) preferred. Preferred
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will be given to candidates with a master’s degree or PhD, are board-certified in Prosthodontics or nearing certification, a track record of research and/or scholarly accomplishments, demonstrated skills