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for Advanced Study (TUM-IAS) funded research collaboration, a Research Associate / Doctoral Candidate (m/f/d) Understanding and Improving Social Interaction in AI-Supported Learning Environments About
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interface of machine learning, deep learning, data science and applications in forest sciences. Together with the Director, you will further develop KIForst as a faculty-wide platform for methodological
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computational approaches to digital education data. The position is funded through a collaborative project between the Hector Research Institute of Education Sciences and Psychology and the Max Planck Institute
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In this position, you will join our Simulation and Data Lab for AI and Machine Learning for Remote Sensing . The lab advances interdisciplinary research and operational services by combining
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. Within this collaborative framework, IDIP provides state-of-the-art high-containment microscopy infrastructure (BSL-2 and BSL-3) and advanced imaging technologies spanning molecular to whole-organism
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Contribution to research on the integration of machine learning into quantum chemical methods and molecular simulation. A particular focus will be on the development, application, and evaluation
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) Implementation and training of an imitation learning model to replicate human delivery manipulations Evaluation of generalization capabilities across different tools and placement locations Testing on the humanoid
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an intelligent, AI/Reinforcement Learning-based system to automatically align the beam transport by adjusting steering mirrors based on camera feedback Investigate the feasibility and trade-offs of relocating
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, and education. Postdoctoral researchers are expected to teach one course per term (co-teaching is possible). The successful candidate will also be encouraged to actively develop collaborations with
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, pathology and outcome data Multi-agent and predictive AI development: Develop machine-learning components for patient-trajectory modelling, recurrence and survival prediction, and integrate them