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the Interpretable Machine Learning Lab (https://users.cs.duke.edu/~cynthia/home.html ) for a scientific developer to work in collaboration with other researchers on machine learning tools that help humans make better
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for this position will be a highly motivated individual with experience in deep learning and medical imaging and a PhD degree in computer science, electrical and computer engineering, biomedical engineering
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. Minimum Requirements: The position requires a PhD in biological sciences, chemistry, or a related discipline and a strong record of publications in peer-reviewed journals. Preferred Qualifications: Ideal
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courses per year. Ideal candidates would have significant prior experience in data engineering, data science and/or machine learning in an industry setting. They would also have a PhD or commensurate
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-performance computing. Additional experience in DNA biophysics, machine learning, and optimization is preferred. This job description intends to provide a representative and level of the types of duties and
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science involving extracellular vesicles. Dr. Kraus’ lab includes researchers with diverse competencies and is a rich environment for learning and growth. Please note this is a term-limited position, ending
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will develop novel statistical and machine learning methods for any of the following: multi-omics data (such as bulk and large-scale single-cell RNA sequencing data, spatial transcriptomics, bulk and
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). Assist with following "lights on" procedures to verify the integrity of collected data and complete the data collection process. (e.g. learn to perform the physiological and instrument calibrations and
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limited to, patient-specific, monthly, daily, and annual QA, machine and equipment acceptance/commissioning, imaging technology, treatment or diagnostic planning, special procedures, and radiation safety
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associate will work on natural language processing (NLP) coding and tasks for a research project at the intersection of machine learning and materials science. The project aims to extract fundamental details