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, Machine learning, Biomedical Informatics or related fields Preferred Qualifications: Experience in developing and training NLP/deep learning models on GPUs (with framework such as PyTorch, tensorflow
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-time (1.0 FTE) Postdoctoral Fellow with a strong background in data science and machine learning. Experience with pediatric cancer and a desire to become a pediatric cancer researcher is highly desirable
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life-long learning. Our faculty have a resolve to create an exciting academic environment that will build upon what is already recognized as one of the finest residency programs in the country, and by
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machine learning applications in ecology, open science ethics and data sovereignty for environmental data, data-intensive exploration of evolutionary processes, big data and environmental justice, or other
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sciences, data science, machine learning, statistics, mathematics, computer science, or related fields. Preferred Qualifications: Experience in at least one programming language such as Python or R
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electron microscopy (sbfSEM). These studies will also require advanced computational analysis of the data as well as the development of machine learning techniques to aid in said analysis. Key
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meetings, present at research meetings, journal clubs, lab meetings (10%) Teach/supervise students, professional research assistants, and other lab members (10%) Developing grant-writing skills by applying
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limited to: Collect data from a range of in vivo physiological and behavioral studies predominantly in genetic mouse models, learn a variety of surgeries, learn gold standard methodologies to study glucose
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biological context and interpretation to characterize chemical mechanism of action; (4) apply machine learning algorithms for identification of biomarkers and classification of environmental toxicants; (5
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early intervention are encouraged to apply. Key Responsibilities: Acquire an understanding of the roles of various disciplines that serve individuals with developmental disabilities and their families