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, interlocking systems. We believe that access to nutritious food and a healthy environment is a fundamental human right. We believe that ensuring a prosperous global future depends on the ability to support local
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include designing and executing experiments to interrogate host-microbe interactions, analyzing and interpreting microbiome sequencing and/or metabolomics data, developing novel computational or analytical
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. Qualifications Completed or soon-to-be-completed PhD in Data Science, Network Science, Computational Social Science or related fields. Solid knowledge in network and Data Science, programming in Python or R, and
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-the-loop exploration of extreme-scale scientific data. This position sits at the intersection of scientific visualization, agentic AI systems, human–computer interaction (HCI), and high-performance computing
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. Essential qualifications PhD in computational statistics, bioinformatics, systems biology, or a related field. Strong expertise in statistical methods, including machine learning approaches, for analysis
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. The candidates are expected to work in a highly collaborative environment with other lab members and industry collaborators. Requirements: Applicants should have a PhD in Computer Engineering, Computer
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PhD in microbiology, microbial ecology, molecular biology, biochemistry, chemical biology or any relevant fields with a dissertation that includes a focus on host-microbe interactions, microbial
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across 50+ departments and programs in the humanities, natural sciences, and social sciences, CAS is a dynamic and interdisciplinary academic community. Our faculty and advisors work closely with students
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an impact on human health and the environment. The mission of the new Electrification for Health program is to improve health through clean electric systems that reduce air pollution indoors and outdoors and
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should meet the following qualifications and possess relevant expertise: A PhD in Physics, Applied Physics, Electrical Engineering, or a closely related field, with a strong experimental research