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Position at the Behavioral Science for Prevention and Care Team (m/f/d) Anticipated Start Date: February/March 2026 About the Behavioral Science for Prevention and Care Team We are a team of social
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integration of the different soil erosion processes on landscape scale. The project “European Soil Erosion Monitoring and Modelling Network for Sustainable Agricultural Land Management” (EUROSION) is an EU
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need for advanced solutions in wound care, the INTROS consortium brings together leading academic and non-academic partners to develop diagnostic and prevention strategies for acute complex wounds
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11.11.2024, Wissenschaftliches Personal In the project “BIG-ROHU” (BIG Data - Rotor Health and Usage Monitoring), a system is being developed which provides information on both the health and the actual stress of helicopter components using a data-based as well as a physics-based approach. In...
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23.10.2023, Wissenschaftliches Personal The Technology and Innovation Management (TIM) Group at the TUM School of Management of the Tech-nical University of Munich, headed by Prof. Dr. Joachim
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of Position Full PhD Working Language English Required Degree Final examination Bachelor Areas of study Financial Management, Insurance, Economics, Accounting, Taxation, Controlling, Economic Sciences
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29.04.2021, Wissenschaftliches Personal This PhD position is in the field of resource management for wireless network that leverage “digital twins” modeling aspects of the physical (such as user
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10.01.2022, Wissenschaftliches Personal The Chair of Computational Modeling and Simulation (CMS) at Technical University Munich invites applications for the position of a Research Assistant (m/f/d) for performing fundamental research in the frame of the project DrawOn funded by the Bavarian...
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, and failure-mode prediction in distributed charging and energy-management environments as part of the BANNER research project Investigate fault-tolerance and fault-recovery mechanisms for decentralized
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prediction in distributed charging and energy-management environments as part of the BANNER research project Investigate fault-tolerance and fault-recovery mechanisms for decentralized edge AI hardware