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, computer science or related disciplines with experiences related to human-AI interaction. KEY RESPONSIBILITIES & ACCOUNTABILITIES The successful candidate will help design and execute studies (online/lab/field
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behavior, human-computer interaction, psychology, computer science or related disciplines to work on research projects on human-AI interaction. Increasing ability to generate human-AI interaction data needs
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community assets using multiple data sources and spatial tools. The role emphasizes project leadership, transdisciplinary research across environmental, social, and political sciences, and interaction with
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emphasizes project leadership, transdisciplinary research across environmental, social, and political sciences, and interaction with state and federal agencies. The appointment is for one year with
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community assets using multiple data sources and spatial tools. The role emphasizes project leadership, transdisciplinary research across environmental, social, and political sciences, and interaction with
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Responsibilities The successful candidate will (1) use microbiological, physiological, ecological, and molecular techniques to study host-symbiont interactions in the shipworm symbiotic model system, (2) design and
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, with a focus on arboviral diseases (e.g., dengue or Oropouche viruses). Other projects include improving risk assessment, optimizing surveillance system design, and developing and evaluating mitigation
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out lab infrastructure, formulating specific research thrusts, and initiating research in robot planning, control, and sensing. Qualifications: Demonstrates the ability to plan and execute research
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to contribute to NIH MIRA-funded research on bacterial surface glycans and their interactions with collectins, key proteins in the innate immune system. This work integrates computational chemistry
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interested in understanding mechanisms driving innate immune responses during host-pathogen interactions, and how commensal microbes shape host immunity in health and disease. Our research combines