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deploying an AI project. This includes initial problem specification, data gathering and analysis, model creation, and implementation. Applicants should be willing to learn and use agentic AI to build and
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unique combination: deep expertise in molecular and computational biochemistry (Moghe Lab; https://www.moghelab.org ) paired with field-tested ecological and evolutionary chemistry (Agrawal Lab; https
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and data from multiple disciplines. ● Experience developing or applying systems-based approaches such as system dynamics, causal modeling, scenario analysis, participatory modeling, agent based
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top-tier venues and will have dedicated time for advancing their own research. The project is in collaboration with CCL (The Center for Connected Learning and Computer-based Modeling, PI Uri Wilensky
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deploying an AI project. This includes initial problem specification, data gathering and analysis, model creation, and implementation. Applicants should be willing to learn and use agentic AI to build and
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for individuals, organizations or society. You will be part of the SAIL research group, whose research activities focus on AI-based modeling of complex systems, uncertainty management in deep learning, visual
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of electrochemistry and artificial intelligence. Ideal candidates will have experience in machine learning, large language models, AI-agent development and computational workflows, with particular interest in building
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, preferably related to serious games and/or agent-based modeling and simulation Desired experience: 2 to 5 years of professional experience Where to apply Website https://www.aplitrak.com/?adid
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, agent-based modeling, or computational models of collective behavior Especially welcome Candidates who combine strong technical methods with serious engagement with social-science theory, or whose
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code Developing agentic AI workflows for specification autoformalization, proof generation, and proof repair Build a strong network in the fields of formal verification, systems, and ML infrastructure