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Max Planck Institute of Molecular Plant Physiology • | Potsdam, Brandenburg | Germany | about 23 hours ago
signals perceived, and how is information transmitted and integrated to ensure plant health, survival, biomass acquisition and seed formation? How can we manage, analyse and integrate complex, large-scale
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networks self-organize their architecture. We are looking for a PhD student (m/f) to join our team at the TUM. Task Flow networks are a fundamental building block of life. Transport by flow is the main task
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of representative failure models for gear failures causes difficulties in their useful lifetime prediction. Critical operational parameters such as loading, speed and lubrication affect the physics of gear meshing
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processes, and the application of AI methods in engineering. Description: Nowadays, computer-aided manufacturing (CAM) methods are used to a large extent for the production of complex machine components, in
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, these systems serve as complex functional approximators trained over an input-output data set. ‘Second Wave AI’ is the term used to describe the current glut of 'machine learning' style intelligence, where
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02.05.2022, Wissenschaftliches Personal Join the team of Prof. Karen Alim at the TUM Campus Garching to investigate how the complex organism-scale behaviour in the slime mould Physarum
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that can find both short- and long-term time dependencies without overfitting and requiring large amounts of data. The methodologies will be developed and validated on complex real-world mechatronic systems
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to use when, and for which amount of energy. Whereas preliminary results are promising, a great many questions and research avenues remain, especially given the complex nature of integrated energy supply
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quantitative data analyses, using complex state-of-the-art analytic techniques (in R and/or Mplus). Dissemination of research findings in the form of peer-reviewed scientific articles, conference presentations
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13.01.2020, Wissenschaftliches Personal PhD position at the Chair of Algorithms and Complexity. Candidate shall work on approximation algorithms for scheduling problems in parallel and distributed