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to the development of remote sensing algorithms, simulation and modeling capabilities, and artificial intelligence/machine learning (AI/ML) methods in support of the goals of the joint NASA/USGS Landsat mission
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geoinformatics and spatial data science, including demonstrated knowledge of GIS, spatial analysis, spatial modelling, and GeoAI. Experience and expertise in WebGIS development, familiar with the core technologies
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antigens presented by MHC molecules. This curiosity-driven project develops cutting-edge AI technology for 3D TCR–pMHC modeling to improve neoantigen identification, TCR specificity prediction, and TCR
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Entitled: “Covalent organic frameworks exhibiting thermally activated delayed fluorescence” Leader Dr inż. Jakub Ostapko The objective of this project is to develop and investigate a new class of self
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understanding of parallel application development techniques (parallel programming models, algorithms, and software) Preferred Qualifications: Experience in implementing ab initio simulation codes such as VASP
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aspects of data collection, dataset preparation, software implementation, model validation, laboratory maintenance, cyberinfrastructure development, and documentation, depending on the role. Conduct
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Postdoc (f/m/d) Methods Development for the Micromechanical Characterization and Modeling of the ...
., finite element simulation, crystal plasticity modeling, analytical/semi-empirical hardening models, or data-driven analysis methods, along with a demonstrated ability to independently develop new
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magnetic resonance imaging (MRI), such as arterial spin labeling and diffusion tractography using programming scripts, such as Python and C++ Self-driven, motivated, and creative in designing image analysis
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 16 hours ago
required, as is the ability to develop and adapt statistical models, conducting diagnostics and management of these data. Familiarity with packaged food and beverage product labelling regulations and
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data driven approaches (experimental dataset physics based model dataset) to achieve process optimization, defect prediction and property prediction in various AM processes. The additional specific