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Your Job: Working with a broad range of imaging modalities (e.g. structural, diffusion-weighted and functional MRI, intracranial EEG) Multi-scale modelling of human brain development Using machine
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processes that produce energy and raw materials. The Department of Thermodynamics of Actinides is looking for a PhD Student (f/m/d) - Machine Learning for Modelling Complex Geochemical Systems. The job
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future scenario simulation of VBD. Including machine learning, statistical, and process-based models. Present findings at scientific conferences and publish in peer-reviewed journals. Contribute
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academic assignments at the chair What we look for in you Completed master’s degree in computer science, transportation, or related engineering fields Solid background in generative AI, machine learning, and
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the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission analysis, and infrared thermography
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modeling and computational workflows Knowledge about machine learning: statistics and deep learning Experience in data analysis, visualization and presentation Good programming skills in languages such as
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the individual process parameters on the target properties and develop predictive machine learning model; iii) based on the machine learning algorithms, develop PBF-LB Mg alloy with defined microstructure
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machine learning We offer: Academic freedom to pursue your scientific interests related to infection biology, inflammation, gene expression, and intracellular organization Competitive salary including
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for machine learning, with research topics ranging from decentralized and federated optimization, adaptive stochastic algorithms, and generalization in deep learning, to robustness, privacy, and security
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-edge Machine Learning applications on the Exascale computer JUPITER. Your work will include: Developing, implementing, and refining ML techniques suited for the largest scale Parallelizing model training