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Field
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integrates real-time data and simulation models to mirror the physical manufacturing and logistics systems. This enables performance monitoring, predictive analysis, and the evaluation of scheduling strategies
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University (ASU) invites applications for two postdoctoral scholar positions in the area of mathematical modeling to work with Dr. Nina Fefferman. The first position will focus on modeling dynamics
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prediction of gene perturbation effects for drug discovery. The successful candidate will play a leading role in developing gene perturbation models that combine foundation models (FMs) and graph neural
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such models, and working with a team of scientists interested in pushing the boundary of predictability. Position Requirements Recent or soon-to-be-completed PhD (completed within the last 0-5 years) in
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, observed and predicted effects of climate change stress the need for adaptative approaches. Climate adaptation strategies are needed to anticipate species vulnerability and management opportunities. In
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | about 17 hours ago
opportunities to model and predict socio-demographic and economic indicators over the life course. This project would combine powerful predictive tools with approaches from causal inference to advance our
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. Combining AI-based prediction (e.g., TCNN, LSTM, etc) with musculoskeletal models to estimate and predict muscle activation and tendon force over short horizons (e.g. ~200 ms). Integrating these predictions
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intelligent decision architectures, predictive analytics, and adaptive computational models that can operate in dynamic, uncertain, and high-stakes project environments. The appointee will conduct original
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Natural History. The researcher will develop deep learning models to predict individual bee age based on wing morphology. This model will be trained of existing wing images and applied to images of museum
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programs-ranging from national infrastructure to major technological rollouts. The project focuses on developing intelligent decision architectures, predictive analytics, and adaptive computational models