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Field
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beginning in fall 2026, preferably with an interest or focus on statistical foundations of data science, artificial intelligence and machine learning, theoretical statistics and probability, uncertainty
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of uncertainty in reward-guided decision-making. 2024.03.27.587016 Preprint at https://doi.org/10.1101/2024.03.27.587016 (2024). 6. Walker, E. Y. et al. Studying the neural representations of uncertainty. Nat
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to illuminate the uncertainties around economies of scale for production and logistics of fuels. Currently there is high uncertainty surrounding the decarbonisation options for energy sectors where molecules
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(Scientific Research Fellow Status) in its current wording. https://www.fct.pt/wp-content/uploads/2026/01/RBi_Republicado_2025.pdf Regulations for Research Grants of the Foundation for Science and Technology in
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working experiences, and professional mentorship and support. The postdoctoral associate will be affiliated with the Center for Avian Population Studies (CAPS, https://www.birds.cornell.edu/home/center
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uncertainties in warming feedbacks on methane, provide improvements that can advance a process-based understanding of feedbacks, and make connections with existing or potential mitigation interventions to reduce
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Contrails are aviation sector’s invisible climate threats with large uncertainties
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language, vision, biomedical knowledge, clinical context, and relevant patient-level data to produce reliable, auditable, and uncertainty-aware outputs. A major focus of the position is the development of AI
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Biophysical and Biomedical Measurement Group, National Institute of Standards and Technology | Gaithersburg, Maryland | United States | 2 months ago
uncertainty. What you will do: - Design, assemble, and characterize DNA origami nanostructures that undergo controlled conformational changes upon target binding and/or applied electrostatic bias. - Develop and
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validating uncertainty-aware AI models for real-time crash risk prediction with guaranteed confidence bounds, interpretability, and fairness-by-design, using a blend of centralized and federated learning