114 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "FORTH" research jobs at Duke University in United States
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, genomics, computer science, bioinformatics, or a related discipline. The successful candidate will lead computational research projects applying advanced statistical, machine learning, and artificial
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doctoral degree in Computer Science or Biomedical Informatics or a closely related quantitative field. The successful candidate demonstrates documented expertise in machine learning and distributed
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, United States of America [map ] Subject Areas: Engineering / Computational Science and Engineering , Machine Learning , Quantum Science and Engineering Appl Deadline: (posted 2026/03/05 05:00 AM UnitedKingdomTime, listed
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the global health scenario and domestically for dissemination, and plenty of opportunities for career advancement. •Learn background/research methods of studies for which analysis is conducted with limited
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of Science in Nursing (BSN) Programs, #2 for Doctor of Nursing Practice, and #5 for Master’s programs, according to U.S. News & World Report. For over a decade, we’ve also been celebrated as a Best School for
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regional leadership in biostatistics, genomics, biomedical informatics, artificial intelligence and health data science. The Postdoctoral Associate will conduct research in statistical machine learning and
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). Duke is committed to encouraging and sustaining work and learning environments that are free from harassment and prohibited discrimination. Duke prohibits discrimination and harassment in
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related field • Strong quantitative background (e.g. ecological theory and mathematical modeling, hierarchical statistical modeling, machine learning, remote sensing, geospatial statistics) • Demonstrated
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) Experimental investigation and computational model simulation of laser-induced bubble dynamics and material damage assessment 3) Developing AI and machine learning models for robot-assisted laser surgery and
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for genomics (e.g., generative models, transformers, agentic workflows) and/or statistical learning (e.g., network & spatiotemporal modeling, functional/longitudinal data, time-series). Analyze single-cell