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Field
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to evaluate algorithms on those benchmarks. Contributing to writing papers and review of the current literature. Other duties as assigned. Qualifications MINIMUM QUALIFICATIONS: A PhD in biomedical sciences
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remote sensing approaches using ocean-color and thermal-infrared satellite observations to study marine organosulfur compounds and ocean–atmosphere interactions. Key research activities include algorithm
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Solution project " ASMADI - AI based Spectrum Monitoring for Anomaly Detection and Identification" to develop signal processing algorithms that enable autonomous detection, classification, and filtering
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biomedical data science, developing new methodology and scalable algorithms, and collaborating with interdisciplinary teams at Duke. Duke is an Equal Opportunity Employer committed to providing employment
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interests. Responsibilities Research will focus on development and application of methods, algorithms and tools for biostatistics and computational biology. A primary goal will be integration of single-cell
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motivated to move the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our team, you get the opportunity to use the latest algorithms in machine learning
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, echocardiography, and/or MRI/CT imaging analysis in pediatric and fetal populations. • Co-lead the development and validation of AI/ML algorithms for fetal cardiac ultrasound image analysis and CHD subtype
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, echocardiography, and/or MRI/CT imaging analysis in pediatric and fetal populations. • Co-lead the development and validation of AI/ML algorithms for fetal cardiac ultrasound image analysis and CHD subtype
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--computational experience in simulating/implementing quantum algorithms for field theories on quantum hardware. Duke is an Equal Opportunity Employer committed to providing employment opportunity without regard
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multiple countries. The position offers a highly collaborative and interdisciplinary research environment. The successful candidate will be expected to: develop computational algorithms for time-dependent