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Field
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of agent-based and/or continuum modelling, analysis and simulation. You will have experience of programming in Python and C++, or demonstrated ability to rapidly acquire fluent knowledge of new programming
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during verbal interactions with human and AI agents. You will be based within the Section for Cognitive Systems, which is a lively and research oriented group of scientists and support staff with a broad
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either or both agent-based modeling and social network analysis/network science. The ideal candidate should be able to program in C or C and have experience working with tera-bytes of data. Preference
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is concerned with the challenging problem of modeling the complex modern radio environment, where a diverse set of devices and agents share the available spectrum. In this environment, it is crucial
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, supply chain management, or a related field. Experience with system modeling or scenario analysis (e.g., system dynamics, agent-based modeling, MCDA, causal mapping). Understanding of or interest in
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provides an excellent environment to publish, expand your professional network, and develop expertise at the intersection of systems modeling, sustainability, and industrial practice. Job requirements A PhD
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of computing and healthcare. Methodologies of interest include: Multi-modal learning Foundation models, including large language models Agentic AI Multi-agent AI systems Transfer learning Self-supervised
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transplantation using mouse animal models. The research involves understanding the mechanisms underlying resistance/relapse following immunotherapy such as CAR T and developing novel agents for protecting
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modules to farmer’s, cooperatives, extension agents, etc. Data scheduling, collection, analysis, interpretation, and presentation. Supervise Postdoc, PhD and Master students as well as interns Project
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of delivering drugs or therapeutic agents to intracellular “undruggable” antigens, thus overcoming conventional antibody-based therapy limitations. Specific Objectives Identify and validate intracellular antigens