189 machine-learning "https:" "https:" "https:" "https:" "https:" "Cardiff University" positions at Zintellect in United States
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phenotyping using both drone-based and ground based sensing platforms. Learn artificial intelligence and machine learning techniques to analyze image and geospatial data from diverse sources for crop monitoring
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-property relationships, statistics and probability, applied mathematics, data science, or machine learning. Application Requirements A complete application consists of: Zintellect Profile Educational and
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Learning about protein design and engineering Exploring cell-based and cell-free screening Applying high-throughput screening Utilizing bioinformatics, machine learning, and other computational approaches
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. Research Project: Joining a team of landscape and fire ecologists to learn about and support geospatial analysis of fire mitigation implementation in the highly fire prone lands of Kona and Kohala on Hawaii
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, the participant will: (1) gain experience in computational modeling to optimize manufacturing high-purity reactive refractory metal powders, (2) learn advanced modeling methods based on density functional theory
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computing facilities at the DOD Supercomputing Research Center. What will I be doing? This project will focus on learning, adapting, and applying US Army Corps of Engineers-developed or supported coastal
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and stress), behavior (grazing behavior halters, accelerometer-based ear tags, chute velocity measures), environmental monitoring, and pasture measures. Learning Objectives: Under the mentor's guidance
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. Description The Office of Global Research (OGR), at the National Institute of Allergy and Infectious Disease (NIAID), National Institutes of Health (NIH), is seeking candidates who are interested in learning
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analysis of laboratory assay readouts, or processing and analyzing transcriptomics data (bulk or single-cell RNA-seq). Learning Objectives: Under the guidance of a mentor, the participant will have the
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the underlying impacts of stressors on bee health and analytical skills for understanding colony level dynamics and predicting mass colony loss events. Learning Objectives: The fellow will learn and apply