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Field
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learning, and AI-driven manipulation. This position offers the opportunity to work on real-world robotic systems and develop novel algorithms at the intersection of robot learning, control, and AI
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starting date is November 2025. The topic of the PhD project will be theoretical research in discrete optimization, with a particular focus on either graph algorithms or multiobjective optimization
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[map ] Subject Area: Applied and Numerical Analysis Appl Deadline: 2025/09/15 11:59PM (posted 2025/08/05, listed until 2025/12/31) Position Description: Apply Position Description Doctoral and
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methods to improve the deployment, adaptation capabilities and safety of robots and critical infrastructures. The developed algorithms will be evaluated on legged robots, wheel-based robots and under
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-photonic computing architectures; Silicon-photonic network architectures Machine Learning Algorithms/Systems: Experience in design and use of ML algorithms; Experience in using ML for designing computing
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, develop novel approaches for proving hardness, and devise new algorithms. You will be expected to conduct individual research and develop research questions, regularly write research articles at a national
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outstanding candidates whose work lies at the intersection of statistics, machine learning, data analytics and modern AI algorithms. This includes, in particular, statistics for high-dimensional and complex
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Science and Engineering, or a related area is required. The position will involve developing models and algorithms for the evolution of inorganic aerosols in the atmosphere, building upon the research
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to: Conduct cutting edge research in machine learning, AI and algorithms, such as but not limited to Bayesian machine learning, human-centered AI and interpretable machine learning, attention markets, gig
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for proving hardness, and devise new algorithms. You will be expected to conduct individual research and develop research questions, regularly write research articles at a national level for peer-reviewed