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Postdoctoral Associate - Birds of the World, Cornell Lab of Ornithology Postdoctoral Associate - Birds of the World Cornell Lab of Ornithology College of Agriculture and Life Sciences Cornell
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24 Apr 2024 Job Information Organisation/Company Forschungszentrum Jülich Research Field All Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Country Germany Application Deadline 19 Jan 2038 - 03:14 (UTC) Type of Contract To be defined Job Status Other Is the job funded...
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Your Job: You will join the Simulation and Data Lab `AI and ML for Remote Sensing,` which aims to enhance visibility in interdisciplinary research between applications from remote sensing and large-scale AI with high-performance and innovative computing. You will conduct independent research on...
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on the topic of "Geodynamic modelling of the Virgin Islands as a proxy for early Earth geodynamics". The successful candidate will become an employee of Durham University. They will join the UKRI NERC-funded
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funded by the national project “Rare-earth single atom MAGnets aNchorEd aT oxIde Surfaces as a platform for new low-consumption magnetic dEvices (MAGNETISE)” financed through the national PRIN-2022 Next
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computer science with specialisation in data science, machine learning or deep learning, or in Earth/Environmental Science with experience in applied data science, machine learning or deep learning. You also will
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: Ecological Effects of Indigenous Land Tenure and Governance (Zavaleta Lab) Position overview Position title: EEB Postdoc: Ecological Effects of Indigenous Land Tenure and Governance (Zavaleta Lab) Salary range
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specialisation in data science, machine learning or deep learning, or in Earth/Environmental Science with experience in applied data science, machine learning or deep learning. You also will have a good track
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missions for passive and active observation of the Earth using microwave sensors and systems. The research targets the retrieval and approximation of bio-geophysical variables of the scattering from natural
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specialisation in data science, machine learning or deep learning, or in Earth/Environmental Science with experience in applied data science, machine learning or deep learning. You also will have a good track