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Field
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at RIBES using machine learning and genomics to overcome linkage drag and accelerate crop breeding by design. You will build models, analyse new sequencing data and optimise strategies for combining
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) positions to join our team. These full-time positions offer a unique opportunity to engage in cutting-edge interdisciplinary research focused on Generative AI within the context of construction robotics
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blades. In this role you will: Design, build and optimise optical and inductive thermal NDE rigs for curved, metre‑scale blade sections; Develop and validate forward–inverse heat‑transfer models
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mathematical information science approaches, such as scientific machine learning. Potential research topics include, but are not limited to: (1) Bayesian estimation of 3D velocity structure models using ocean
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outstanding postdoctoral researchers in the fields of Physics, Chemistry, Mathematics, Computer Science, Earth Science and the Life Sciences. This collaborative program offers a comprehensive four-year position
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infrastructure, and the chance to shape the direction of innovative silicon photonics technologies. It is an ideal opportunity for those passionate about bridging fundamental research with practical, scalable
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safety at ORNL and DOE sites. This position resides in the Performance Engineering group in the Data and AI Systems Section in Computer Science and Mathematics division within Computing and Computational
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21 Aug 2025 Job Information Organisation/Company MOHAMMED VI POLYTECHNIC UNIVERSITY Research Field Computer science Engineering Researcher Profile Recognised Researcher (R2) Established Researcher
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and papers for presentation at conferences and workshops under the direction of the Principal Investigator or Grant-holder. To assist with the development of research objectives and proposals
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programming skills in Python are essential, along with the ability to design experiments, analyze results, and interpret findings. Knowledge of optimization techniques, statistical modeling, and data management