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Field
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to joint research activities, publications, and surveys. Requirements PhD degree (or near completion) in robotics, control, machine learning, or a related field; Strong publication record demonstrating
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Degree PhD Course location Kaiserslautern Teaching language English Languages Discussions are held in English (100%). Programme duration 8 semesters Beginning Only for doctoral programmes: any time
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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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algorithms and data structures, machine learning, computer graphics and vision, database systems, artificial intelligence, logical methods, programming languages, computer architecture, and security, to name
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research on exciting projects and develop customised products and services for our clients from numerous industries and the public sector. The overarching topics at Fraunhofer ITWM are machine learning
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-XRF, Raman, FTIR in reflection mode) to enable multimodal data fusion and automated material characterization. • Apply and further develop machine-learning and statistical models (e.g. PCA, SAM
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systems in a targeted manner. An important aspect of this effort is the accurate organization, harmonization, and exchange of research data that will fuel the application of machine learning approaches
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Max Planck Institute for the Study of Societies • | Koln, Nordrhein Westfalen | Germany | 2 months ago
. Tuition fees per semester in EUR None Combined Master's degree / PhD programme No Joint degree / double degree programme Yes Description/content The International Max Planck Research School on the Social
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for improved understanding of structural and kinetic processes in electrolytes; and machine learning concepts for improved analysis of experimental and simulated data. Material Synthesis Within this research
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of molecular and biological matter using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts