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surveillance and preparedness planning using multiple modeling approaches. The successful candidate will develop and implement statistical and machine-learning models, integrate multi-source ecological datasets
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Description Our Commitment Texas A&M University is committed to enriching the learning and working environment by promoting a culture that respects all perspectives, talents & lived experiences. Embracing
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researchers with numerous opportunities for learning and research collaborations. Lake Nona Medical City, located in Orlando, Florida, is a health and life sciences campus near Orlando International Airport and
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Center for Biologics Evaluation and Research (CBER) | Southern Md Facility, Maryland | United States | 8 days ago
with advanced machine learning approaches. The research will involve assay development, metagenomic (mNGS) sequencing, and bioinformatics analysis to advance regulatory science and enhance the safety
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processing, machine learning, and optimization theory. Strong verbal and written skills in English. Excellent analytical and problem-solving skills, and capacity to pursue independent research as
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computational models for industrial capacity planning, logistics optimization, material flow analysis, and supply chain analysis. Apply artificial intelligence, machine learning, LLMs, and advanced statistical
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machine learning approaches with large-scale biological data to automate genome curation by detecting, interpreting, and correcting structural errors, reducing manual effort from weeks to minutes thus
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computing, machine learning for hardware design, integrated circuit design, or hardware–software co-design. Experience with semiconductor design tools, circuit/system modeling, or large-scale hardware design projects
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will primarily work on interdisciplinary projects to examine how computing students develop and enact ethical agency within the context of human-computer interaction (HCI) and user experience (UX) design
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that combines modern machine learning approaches with large-scale biological data to automate genome curation by detecting, interpreting, and correcting structural errors, reducing manual effort from weeks