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spatial analysis and mapping tools (e.g., QGIS, ArcGIS, or spatial packages in R/Python) Interest or experience in applying AI or machine learning methods to ecological questions Personal attributes: Strong
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are generally costly to repair, methods that can precisely and rapidly locate faults or even faults under development are of great value. Localization of very critical cable sections that are close to failure
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criteria Experience with large C++ code bases Experience with MLIR and/or LLVM frameworks Experience with Precision Tuning and/or other approximate computing methods Experience with one or more heterogeneity
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, power, specific topologies, their control methods and suitable power semiconductors technology. The PhD candidate will work in the 300 MNOK Centre for Environment-Friendly Energy Research (FME) “Maritime