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Field
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: development and coordination of the wind erosion monitoring program, the development and adaptation of measurement methods and modelling approaches both in the ZALF part of the project and between the involved
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for Experimental biology (Poland). Dioscuri is a program initiated by the Max Planck Society, managed jointly with the National Science Centre (Poland) and mutually funded by the Polish Ministry of Science and
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. Your responsibilities Work with genetically modified mouse models Culture cell lines, iPSCs, and renal organoids Analyze transcriptome and proteome data Apply high-resolution microscopy techniques Your
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on disaster risk management and climate adaptation, using probilistic risk modelling, applied statistical methods to evaluate risk management and adaptation measures in the agricultural sector, mainly in low
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degree or PhD in Computer Science, Electrical Engineering, Control Systems, or a closely related field. Experience in reachability analysis, formal verification/model checking, control theory, or related
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benchmarking of clay mineral surface finite models for DFT simulations Speciation simulations of the radionuclides in various environments Your profile Completed university studies (Master/Diploma) in the field
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Potsdam, Brandenburg | Germany | about 2 months ago
Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Area of research: Scientific / postdoctoral posts Job description:PostDoc in
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Work group: ATLAS Area of research: Scientific / postdoctoral
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Models for Real-World Healthcare (MLCARE project DC3). The position is funded by the MSCA Doctoral Network MLCARE (Machine Learning Computational Advancements for personalized mEdicine). The MLCARE
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Student or Scientific Assistant for Remote Sensing Data Processing and Cloud-based Workflows (f/m/d)
of existing EO workflows for large-scale or automated processing Assistance with preparing, cleaning, and organizing reference datasets for model training and validation Documentation and structured preparation