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research activities involving: Chemical, biochemical, histochemical and immunohistochemical analyses. Microbiological and molecular analyses for the diagnosis of infectious agents. Parasitological
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to drive autonomous, coordinated and efficient satellite operations. . Main Research Topics Onboard Agentic AI for Mission Planning and Autonomous Management Develop onboard AI systems possibly based
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software for quantum-chemical simulations based on AI and ML methods, including defining and creating AI agents, testing methods, and large-scale calculations We offer employment as a university professor in
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application: Experience with agent-based modelling, network modelling, dynamic systems, spatial interaction models, activity-based travel modelling, transport simulation, or digital twins. Experience with
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 13 hours ago
, developing processes and procedures for monitoring, alerting, detection, and response functions for on-premise, cloud-based, and, as appropriate, third-party systems and services. Review system logs and real
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autonomous systems that collaborate effectively while controlling what outside observers can infer? In this PhD project, you will develop security-aware planning and control methods for multi-agent cyber
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-resilient, high-yielding and nutritionally enhanced crops, while enabling the innovative plant-based production of non-native highvalue biomolecules (e.g., growth factors for biomedical and food applications
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We are offering a PhD fellowship in “Agentic AI and Foundation Models for Global Pathogen Analysis” commencing September 1st, 2026, or as soon as possible thereafter. Our group and research
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and collaboration with Meany staff, visiting artists, agents, faculty, and partners. Administration of the k-12 Student Matinee Program – 10% Oversee the promotion, registration, placement and
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project on transparent, agent-based AI methods to support multidisciplinary tumor boards in oncology. You will develop methods to transform heterogeneous oncology documentation into structured, time-aligned