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the subtropics in Latin-America. The research programme will examine productivity of grasslands, nutrient stocks and cycling and their relationship to biodiversity. We conduct experiments in the field
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– depending on the successful candidate’s background and interests. Your tasks: Develop new exact and approximation algorithms and perform complexity analyses for optimization problems on (temporal) graphs
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synthesized responses generated by AI-driven search engines? How does recommendation sentiment change with content presentation? Can we develop quantitative and qualitative metrics that accurately forecast
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scientific development of this Working Group to support the Food Systems Biology approach at the Leibniz-LSB@TUM • Acquisition of third-party funding and scientific management of the research projects
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, conference participation, and doctoral training are available. Candidates are expected to participate and successfully complete the doctoral program at the TUM School of Management. Further information
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to remote sensing and simu-lation modeling. A particular focus of our work is on mountain forest ecosystems. A quantitative understanding of ecosystem dynamics provides the foundation for the development
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research studies for automated image analysis. In particular, you will: Plan, develop, and implement AI/ML algorithms for pathology image analysis. Integrate multi-modal data (e.g., genomics, clinical data
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at the forefront of technology. As a key member of the detector team, you will play a leading role in the development, integration, and commissioning of complex detector systems for newly planned or upgraded
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vibrant and interdisciplinary research environment at TUM Access to unique datasets and collaboration with a well-established European network Opportunities for professional development and academic career
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pages or friendships between users in a social network. Due to the large variety in data science tasks performed with graph-structured data, different specialized systems have been developed, such as