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algorithms for application parallelization, simulators and virtual platforms for application- and architecture exploration, hardware/software co-design and operating/runtime systems. Typical application
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link structure-property relationships from DFT, MD, phase-field, TEM/SEM, and other multimodal datasets from simulation and experiment Develop benchmarking protocols and toolkits to evaluate AI models
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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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discipline boundaries and abstraction levels is a must. Knowledge in integrated circuit design, testing and simulation using Cadence is a plus. Knowledge of digital neuromorphic hardware and sensors is a plus
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-free double perovskites Your Profile: Master`s degree in theoretical or computational physics, chemistry, materials science or similar fields Familiarity with atomistic simulations, high-performance
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other multimodal datasets from simulation and experiment Develop benchmarking protocols and toolkits to evaluate AI models on materials science tasks as well as integrate your semantic-AI services
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of new EEG and MEG neuroimaging and mc-tCS simulation approaches based on realistic head volume conductor models using modern finite element methods as well as sensitivity analysis. The new methods will be
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, disabled candidates will be given preference. Please upload complete application documents (cover letter, curriculum vitae, certificates, list of MSc courses and grades, copy of the master thesis, reference
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and the effects of disordered correlated microstructures on diffusion; iii) development of energy-based models and numerical simulations of hyperuniform assemblies; iv) development and application
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the MATSim agent-based transport simulation framework. The main task is to enable simulated agents to choose transportation modes, such as car, bus, bike, or walking, based on real-time feedback from