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Field
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, safe and socially just energy supply system based on renewable energies. We contribute to this with our research priorities of energy supply, energy distribution, energy storage and energy use. We
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? You have some experience in research and are familiar with maritime navigation or optimization algorithms? Great! You also have solid Python skills and enjoy working analytically and documenting your
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an extensive safety analysis and calidation of perception algorithms in automotive. Through our work, we lay the foundation for a reliable digital future. What you will do In our Trustworthy Digital Health group
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microscopy and atom probe tomography will be prepared. Finally, you will merge the images by means of deep learning algorithms. Your tasks in detail Development of the experimental protocol for the imaging
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assistance systems Collaboration in the development of AI algorithms (LLM, fine-tuning, RAG, AI agents, embeddings) Literature research on the topic of AI What you bring to the table Studies in
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. Particularly, we would like to address mixed-phase processes in deep convective clouds to understand how these clouds interact with aerosol: How do deep convective clouds affect the aerosol size distribution and
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, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids and thermal energy systems for a sustainable
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these micropollutants, per- and polyfluoroalkyl substances (PFAS) are of particular concern. Like microplastics, PFAS are highly persistent, mobile, and widely distributed, even in remote areas. Both substance groups
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, and socially just energy supply system based on renewable energies. We contribute to this with our research focuses on energy generation, energy distribution, energy storage, and energy utilization
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algorithmic algebra. For more information about the TUM Department of Mathematics, please visit our website: https://www.math.cit.tum.de/en/math/home/. The position is a full-time position (100%), initially