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collaboration, this position is based on campus, full-time, at Harvard University. Remote work for this position is not possible. Basic Qualifications PhD in computer science, statistics, electrical engineering
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dynamics and agent-based modeling approaches. Demonstrated ability to communicate complex technical findings to both scientific and applied audiences. Proven success mentoring undergraduate or graduate
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work with a multidisciplinary team to advance agentic AI tools for simulation, interpretation, data analysis, and scientific discovery. The appointment is expected to last two years and the contract is
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and physical modelling. The goal of this position is to develop data-driven approaches to AI-based analysis of complex interaction systems and suitable hybrid architectures for this purpose
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trial design, dose-finding methods, phase I/II trial designs, model-assisted or model-based trial designs, or oncology clinical trials. Prior publications or preprints in biostatistics, statistics
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PostDocs on the development of cutting-edge AI-ready/agentic infrastructure for data and model discovery, model metadata extraction, and scholarly intelligence. The project will explore conceptual frameworks
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agents. The Postdoctoral Associate will work as part of a highly integrated research team utilizing a variety of laboratory technologies and approaches. Specialized skills in molecular/cellular biology and
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++, or JavaScript Experience with AI or machine learning techniques, including large language models or agentic systems Experience developing or integrating interactive visualization systems, including web-based
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for Vertebrate Genomics - providing exceptional opportunities for collaboration, mentorship, and intellectual exchange. Anticipated Division of Time 80% Research: Build, train, and evaluate cutting-edge AI models
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”. The main objective of the SPAN network is to address this need by prioritizing the testing of different neuroprotective agents in humans based on their measured comparative efficacy in experimental stroke