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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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groups to apply. Applications should be sent by e-mail, together with significant documents (Your application should include a cover letter, your CV, a copy/scan of your degree and course transcripts
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at the nanometer scale. We will use available 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
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atomistic simulations, high-performance computing, and the application of AI-based methods Basic knowledge in photovoltaics and solid-state materials for energy application Ability to work individually and in
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resource-efficiency requirements. This collaborative doctoral project brings together the Institute of Advanced Simulation – Materials Data Science and Informatics (IAS-9) and the Institute of Energy
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Project (PhD Position) – Quantum-Classical Co-Simulation Framework Development for Neurobiological Systems Your Job: The overarching goal is to implement a code for multiscale quantum mechanics / molecular
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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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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
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Your Job: The overarching goal is to implement a code for multiscale quantum mechanics / molecular mechanics (QM/MM) molecular dynamics simulations using a Quantum Centric Supercomputing (QSC