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exploration, optimization, and search algorithms in extremely complex and enormously large spaces motivated by physics and chemistry (RL, BO, Large-Scale Ansatze, …) AI-driven discovery of hardware for some of
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
predictive machine learning model; iii) based on the machine learning algorithms, develop PBF-LB Mg alloy with defined microstructure, improved mechanical and corrosion properties. Research stays are planned
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motivation in conducting evolutionary and chemical ecological research at different levels. •MSc/diploma in a relevant field (e.g., evolutionary biology, chemical ecology, sensory biology). •Strong experience
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sensitivity analysis, impact of the individual process parameters on the target properties and develop predictive machine learning model; iii) based on the machine learning algorithms, develop PBF-LB Mg alloy
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computing to develop a continuous and local alternative to existing gradient-based learning rules, bridging theories of predictive coding with event-based control/ Simulate models of the learning algorithm
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. We are working
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of superconducting qubits to quantify performance and identify limiting physical mechanisms Perform quantum device calibrations, benchmarking, and run quantum algorithms Presenting and publishing the research
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the neighbouring MPI-BI are devoted to basic research on topics in behavioural ecology, evolutionary research and neuroscience. Around 500 employees from more than 50 nations study how animal organisms acquire
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the individual process parameters on the target properties and develop predictive machine learning model; iii) based on the machine learning algorithms, develop PBF-LB Mg alloy with defined microstructure
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24.09.2025, Wissenschaftliches Personal The Chair for Efficient Algorithms, led by Prof. Stephen Kobourov, invites applications for a fully funded PhD position at the Technical University of Munich