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Karlsruhe Institute of Technology (KIT) | Karlsruhe, Baden W rttemberg | Germany | about 12 hours ago
test non-invertibility using machine learning attacks Protocol design. You conceptualize a proof of physical work protocol and design attack strategies against it Blockchain simulation. You simulate a
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Job Offer from September 15, 2025 The International Max Planck Research School for Sustainable Metallurgy offers 6 PhD positions (m/f/d) in Sustainable Metallurgy (Experiment & Simulation
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workflows for descriptor based microstructure reconstruction to identify material parameters for crystal plasticity simulations from experimental data through inverse analysis to establish structure–property
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-body positron emission tomography (PET) with magnetic resonance imaging (MRI). In conjunction with the development of algorithms, dedicated software and hardware-based simulations will be developed
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applications. Your main tasks: Develop and integrate degradation models for multiscale and multiphysics simulations of solid oxide cells Validate models using experimental data (e.g. IV curves, EIS measurements
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degradation models for multiscale and multiphysics simulations of solid oxide cells Validate models using experimental data (e.g. IV curves, EIS measurements) Apply ML methods in combination with CFD
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Protocol design. You conceptualize a proof of physical work protocol and design attack strategies against it Blockchain simulation. You simulate a blockchain network based on this protocol and analyze its
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simulation. Description of the PhD topic (subproject B7 - New methods for multimodal microscopic simulation of street users’ behavior in shared space contexts): This PhD project will develop and implement
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material parameters for crystal plasticity simulations from experimental data through inverse analysis to establish structure–property linkages based on numerical simulations and to transform them into AI
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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
DNA thermodynamic database, coarse-grained simulations of DNA motifs, and existing experimental data to establish an AI model that is able to guide the construction of desired secondary structures