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, studying health-related (mis-)information on social media and its impact on young adults. The position includes international research collaboration, methodological training, and a supportive work
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failure mechanisms. The performance of the developed methods will be evaluated using real operating data. In addition, it will be investigated how reliability and safety conditions can be taken into account
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on Responsible Data Science. The PhD positions will be at the intersection of Data Science and Social Sciences and will focus on topics such as Explainable & Fair AI, AI Auditing, AI Alignment, and AI Safety in
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efficient and safe trajectory planning in safety-critical scenarios. For this purpose, we focus on modeling and quantifying risks in order to subsequently incorporate them into trajectory planning. The goal
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(m/f/d) in the topic: “AI-based processing of CAD models for automated planning of computer-aided manufacturing.” The candidate has the opportunity to pursue a doctoral degree (Ph.D.). Remuneration is
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privacy-preserved fashion. Research topics include, but not limited to, i) handling distributed DL models with data heterogeneity including non i.i.d, and domain shifts, ii) developing explainability and
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• Experimental investigations using atomic force microscopy (AFM), including force-distance curve-based imaging, (single molecule) force spectroscopy, nanomechanics, and associated data analysis • Application
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08.09.2021, Wissenschaftliches Personal The Professorship of Machine Learning at the Department of Electrical and Computer Engineering at TUM has an open position for a doctoral researcher (TV-L E13
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research in the broad field of computational methods for the built environment. Particular emphasis is placed on building information modelling, digital drawings, point cloud capturing and processing as
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-situ measurement network and perform terrestrial laser scanning, analyzing microclimate data and their relation to forest structure, and using optical satellite time series and radiative transfer models