182 master-"https:" "https:" "https:" "https:" "UCL" Postdoctoral research jobs at Nature Careers
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of Agroecology, our main goal is to contribute to sustainable solutions to some of the world’s biggest problems within the areas of soil, plants, animals, humans, and the environment. We want to make a difference
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, conducting research, analyzing data, preparing the work for publication and disseminating results. The work of the post-holder is expected to lead to high-impact publications. Your main tasks and
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: Successfully completed university degree (diploma/master's) in chemistry, materials science, physics, or engineering Doctorate Practical experience in the safe handling of organic chemicals Experience with
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with digital technologies in relation to site-specific environmental, technical and socio-economic data, including remote sensing Who we are At the Department of Agroecology, our main goal is to
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international collaboration partners Support and administer internal web and Linux servers Your Profile Academic degree (master's and Ph.D.) with a background in computer science, bioinformatics, physics
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or machine learning, proficiency in deep learning techniques (CNN, VIT, diffusion, GAN) Good understanding of the mathematical foundations of machine learning Mastering python and related AI software
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genomics, RNA labeling/sequencing techniques, TMT mass spectrometry, various cellular and molecular assays, and a one-of-a-kind biorepository of primary and metastatic human prostate and bladder cancer
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culture of collaboration, innovation, and resilience, valuing diverse expertise to drive sustainable solutions to humanity’s enduring challenges. Wellcome SynHG Professor Chin is the lead Principal
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Postdoctoral Researcher Position in Ecological Knowledge-Guided Machine Learning at Aarhus Univer...
healthy work-life balance. Place of work and area of employment Main campus of Aarhus University at C.F. Møllers Allé 3, 8000 Aarhus C, Denmark Contact information For further information, please contact
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aerosol modules, and assess the importance of different processes with a comparison to available observations. Analyse large model output and observational datasets to determine the impacts and main drivers