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Post-doctoral Position in AI Causal models for Synchrotron Anomaly Detection H/F This post-doctoral position is part of a collaboration between LIAD (Laboratory of Artificial Intelligence and Data
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computing AI on High-Performance Computing (HPC) cluster. Examples on areas of research interest include but are not limited to: Vision transformers AI foundation models Computing and energy-efficient
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with partners across Europe: data sharing, code exchange, joint publications and reporting. Your qualities You hold a PhD (or near completion) in Soil Science, Environmental Modelling, Biogeochemistry
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modeling and characterization for communication and sensing in emerging spectrum for 6G and beyond, with a focus on the FR3, THz and optical frequency bands. This research will be conducted under the joint
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of the microbiome in olfaction using mouse models. The selected applicant will join the vibrant and friendly Tucker lab and work as part of a team interacting with the group of Prof Mike Curtis. The postdoc will
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(SDPs). You will design climate change mitigation scenarios that respect both climate targets and sustainable development goals using the REMIND model, one of the world’s leading integrated energy-economy
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using advanced geological modeling tools such as Datamine software, Leapfrog Geo and Surfer. Supervise MSc/PhD students working on related tasks. Publish high-impact papers and contribute to funding
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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form, how it is generated and how it evolves. In particular we focus on the evolution and evolvability of vertebral counts, and we use various species of Lake Malawi cichlids as our model organism
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this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD qualified in relevant subject area* Experience developing deep learning segmentation models