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Field
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-related applications Data protection in machine learning (e.g., federated learning, differential privacy) Monitoring and verification/validation of Al-based systems at runtime Trustworthy Al engineering
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, artificial intelligence (AI), and socio-economic analysis. This program will equip them with advanced expertise in reservoir modelling, machine learning, advanced oxidation processes (AOP), and microbial
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parameters, digital twins, as well as complex nonlinear problems where AI-based methods such as deep learning are used to obtain better predictions. Connections to machine learning methods are primarily
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project “Analytics for Learning with Machines” (ALMA) The position is TV-L E13, 75%, limited to 3 years, funded by the Deutsche Forschungsgemeinschaft (DFG). The project is a Franco-German collaboration
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problem. Do a theoretical analysis of the assigned problem using tools from information theory and related fields. Design a solution which is implementable on a computer and in hardware. Collaborate with
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fields. Design a solution which is implementable on a computer and in hardware. Collaborate with colleagues to implement the solution in hardware at the ACES lab at the Institute of Theoretical
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the work. The results are verified by a targeted deactivation of the identified neurones and then compared with randomly deactivated neurones. What you do with us: Researching and implementing novel machine
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Manipulation in Cluttered and Dynamic Environments (ID: TUEILSY-PHD20240930-SCMM) A more detailed topic description can be found at https://www.ce.cit.tum.de/lsy/open-positions/open-phd-positions/ . Requirements
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present. Evaluation of the trained models on suitable datasets. What you contribute Good knowledge in the field of machine learning and training neural networks. Good Python skills, preferably some
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civil and military operations“ and „operational analysis and evaluation“. The combination of these research focus areas provides an ideal platform for interdisciplinary research in simulation and