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allow users to input CDR forcing (e.g., alkalinity addition) and produce day-by-day forecasts of CO2 uptake and storage durability. The project combines physics-based modeling, machine learning, and high
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. MATLAB, C/C++, Python. Highly motivated and keen on working in an international and interdisciplinary team. Applicants with strong background in the following fields are preferred: Machine Learning Formal
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candidates with strong expertise in Bayesian methods, uncertainty quantification, and/or machine learning applied to nuclear theory. The group’s research spans a wide range of topics including nuclear
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and methods for advancing the research effort Design and carry out computer experiments on deep learning and related robotic simulations Collaborate with other engineers to create prototypes of embodied
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) COFUND scheme. Around 15 postdocs will be recruited in the fifth call 2026, with each fellowship lasting 36 months. AMBER has six core partners: Lund University/MAX IV, Sweden, the European Spallation
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., machine learning for quantum error prevention/mitigation/correction) Quantum machine learning Quantum cloud technologies We are actively involved in practical applications through partnerships with
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applications for a Postdoc (m/f/d) in the ERC project “Algorithmic Governance – A Public Perspective” (AGAPP). About us The Munich School of Politics and Public Policy (HfP), with its affiliation
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Description: Apply Position Description We invite talented and motivated applicants for PhD and Postdoc positions in the group of Haowei Xu (https://www.haoweixu.com/ ) at the Department of Physics, City
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researchers working on hyperspectral imaging, radiative transfer modelling, machine learning, agronomy, and plant genetics. You will also work with HYDRA-EO partners in Netherlands, Spain and Italy
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State University and work closely with I-CREWS researchers across the state. The position emphasizes developing, integrating, and applying modeling approaches-including machine learning (ML), hydrologic