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, biomedicine, and other areas of societal importance. Coding and/or machine learning experiences are highly valued. Specific projects may involve developing multiscale simulation methods for quantum mechanical
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) Cleaning and managing large datasets from administrative data sources or online learning platforms Causal machine learning (e.g., double/debiased machine learning (DML), causal forests, generic ML) Learning
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, including analyzing metagenomic data (e.g., virome) and phylogenomics, statistics, and an interest in infectious disease research. The ability to develop novel computational methods using machine learning
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, or robotics. • Knowledge of artificial intelligence, machine learning, computer vision, • sensing, data analytics, simulation, human-technology interaction, or cyberinfrastructure. • Knowledge of construction
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) mathematics, physics, or a related STEM fields. Strong programming and data analysis skills (e.g., Python, R) Solid understanding of machine learning, deep learning, and data modeling techniques Job Description
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applications for a fully funded postdoctoral associate position. This position, available immediately, focuses on developing machine learning and deep learning methods for analyzing large-scale single-cell DNA
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well as general research involving the application of methods from theoretical physics, mathematics, and machine learning with the goal to understand the brain function. Position Requirements Applicants
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 2 months ago
Education & Experience: PhD in Computer Science, Visualization, Cartography, Geographic Information Science, or a closely related field. Strong background in visualization, computer graphics, or perceptual
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About the Opportunity SUMMARY The lab of Professor Albert-László Barabási is looking for Postdoctoral Research Associates in the area of network science, nutrition, biological networks, machine
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)-statistics, (applied) mathematics, or a related STEM field. Prior working experience with EHR data, machine learning, NLP, bioinformatics, and large language models (LLM) is preferred. In particular