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Field
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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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, and multimodal modeling of protein function and cellular state. We seek candidates with strong technical preparation in modern AI/ML, a demonstrated record of scholarly achievement, and experience in
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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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knowledge of developing AI-based information systems, such as AI-enabled engagement e.g., agentic AI and AI-enabled insight generation e.g., machine learning analytics in both individual and organizational
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SciLifeLab. The successful candidate will work closely with Avlant Nilsson cancer cell modeling lab and Wei Ouyang’s AICell lab who together will develop the first foundation cell model based on HPA and other
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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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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 1 month ago
Federated Energy Research Accelerator (AFERA) framework. This fellowship offers a unique chance to engage in research at the intersection of Agentic AI, high-performance computing, and digital engineering to
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supervision of PI Calina Copos and will engage in collaborative work with cell and developmental biologists. Expertise in agent-based models, continuum PDE descriptions, dynamical systems, and/or ML-based
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simulation, including O/D modeling, multimodal network modeling, agent-based or behavioral modeling Large-scale computing, cloud-native analytics workflows, and data engineering for mobility platforms AI/ML
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Develop industrial process digital twin models based on the fusion of mechanistic and data-driven approaches. Develop predictive maintenance and fault diagnosis algorithms for critical equipment (e.g