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Postdoctoral Fellow on the Croatian Science Foundation (CSF) project ‘Quantifying impacts of plastics on aquatic and terrestrial organisms (QPlast)’ in the Laboratory for Informatics and Environmental Modelling
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Computational Postdoctoral Fellow (Quantitative Modeling Group) - 106785 Division: BE-Biological Systems & Engineering Berkeley Lab’s (LBNL, https://www.lbl.gov/) Biological Systems and Engineering
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resilience planning for the Treasure Valley. Unit URL https://iwrri.uidaho.edu/ Position Qualifications Required Experience Experience working with quantitative analysis, modeling, or data-driven methods
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of stress intensity factor evolution at the crack tip. Concurrently, a numerical model will be developed to complement the experimental results and allow for the calculation of crack propagation rates. Work
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conduct research related to creating or testing deep learning models for genomics, exploring new techniques related to spatial simulations, or other topics discussed with the PI. Basic Qualifications Core
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: Software Engineering, Sensor Networks and Engineering Computing and the HVL Software Engineering Group (https://www.hvl.no/forsking/gruppe/programvareutvikling-software-engineering/). The research programme
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. HARPNET’s scientific programme is integrated across three scientific work packages, where data, technologies and biological models will be shared across projects through joint supervision, network activities
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empirical perspectives. The NOMIS Fellowship Program supports groundbreaking research projects related to how images act as models or paradigms in scientific and aesthetic contexts. We are interested in
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to more than one; state your preference in your motivation letter. 1. Neurodevelopmental proteomics You will map the molecular circuitry of human neurodevelopment using advanced 2D and 3D cell models together
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, protein biochemistry and/or cancer biology. Experience with CRISPR genome editing, mouse models or omics technologies is considered an advantage. Contact(s) for information on the position (identity