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of artificial intelligence , traffic management, and decision support systems. The successful candidate will explore the application of foundation models, such as large language models (LLMs), to support and
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Carl von Ossietzky Universität Oldenburg | Oldenburg Oldenburg, Niedersachsen | Germany | about 2 months ago
team spirit Good communication skills Experience programming in python Experience in computational modeling of neural circuits and in the mathematical analysis of neural computations Research experience
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Targeted Project Complexflows, which aims to promote and structure the interactions of mathematics with other sciences around current issues. The thesis will be co-directed by F. Radjaï (LMGC, ED I2S 166
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Ruiz and collaborate closely with academic and industrial partners across disciplines and sectors. In this role, you will: Design and perform lab-scale pyrolysis experiments with industrial and model
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can also tailor your employment conditions through our Terms of Employment Options Model. In this way, we encourage you to keep investing in your personal and professional development. For more
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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
, applied mathematics, or a relevant engineering discipline Good programming skills and experience with numerical modeling Interest in performing experiments Excellent written and spoken English skills High
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of how alternative land management practices impact greenhouse-gas fluxes through the development and application of sophisticated modelling tools. The work will involve model development on the Cambridge
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Are you eager to perform cutting-edge molecular modeling to design plant-based dairy alterantives? Then, this position is for you. Job description You will join a unique project which aims
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geometry can be reconstructed mathematically (this is called inverse scattering). This requires both sophisticated mathematical models and efficiently implemented algorithms. In the case of wafer metrology
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-edge infrastructures, and emerging AI-driven user applications. Key research directions include: Modeling and profiling of emerging AI-based workloads and data-intensive applications in mobile networks