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and Atlas Mapping. The position is one of four in a coordinated cluster hire - alongside colleagues in behavioral neuroscience, machine learning and AI, and research software engineering - studying
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concepts about biological processes, advance information technologies and human-machine interactions and, last but not least, provide new insight for designing efficient strategies for teaching and learning
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): · Hybrid Multiscale Modelling · Hybrid Physics-Machine Learning Analyses · Coupled Atmosphere-Turbine Models · Uncertainty Quantification in Hybrid Frameworks We offer the opportunity to work in a very
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of system and data confidentiality and complete any other requirements. Desirable skills: Experience in programming (C, python, or similar). Knowledge in machine learning or distributed systems. How to apply
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research excellence and the ability to pursue a doctoral degree at TUM Documented experience in machine learning and/or natural language processing with deep knowledge of LLMs, RAG and agent-based AI systems
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of different concepts. This endeavour is typically accompanied by new insights and synergetic effects due to the inherently different viewpoints of the previously separate fields. Our task force on machine
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work with the UK semiconductor industry. The studentship represent a unique opportunity to be trained in the epitaxy process and to work in an emerging and exciting area of combining AI/machine learning
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-of-the-art methods such as optogenetics, connectomics or machine learning. Activate map To activate the map, click on the "Show map" button. We would like to point out that data will be transmitted
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Intelligence/Machine Learning (AI/ML) methods in agriculture (Agro-AI/ML); and Experience in programming with multiple languages (e.g., Java, C/C++, Python) for geospatial information systems, agro-informatic
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system for ferry quays, containing labelled damage data as training material for a machine learning model capable of automatically classifying structural damage from drone inspection images. The project