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quasiperiodic potentials, requiring modeling techniques capable of handling extremely large system sizes. In this project, we develop algorithms based on active-learning tensor-network tight-binding strategies
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. Viktar Asadchy[AALTO] Co-supervisors/mentors: Dr. Victoria Tormo [INDRA] and Dr. Barthès [3DEUS] Objectives To establish an analytical modeling approach for multilayer tunable metasurfaces that captures
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approaches and optimization System dynamics modelling Energy system resilience and risk assessment The research will heavily involve mathematical model development and the use of specialised software
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intelligent surfaces Main supervisor: Prof. Viktar Asadchy[AALTO] Co-supervisors/mentors: Dr. Victoria Tormo [INDRA] and Dr. Barthès [3DEUS] Objectives To establish an analytical modeling approach
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and time-varying performance through quantitative comparison with analytical modeling and full-wave simulation results. This position is part of the MetaTune Doctoral Network "Reconfigurability using
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comparison with analytical modeling and full-wave simulation results. This position is part of the MetaTune Doctoral Network "Reconfigurability using inversely designed metasurfaces", which has been funded
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
23 Jan 2026 Job Information Organisation/Company AALTO UNIVERSITY Research Field Computer science Engineering Mathematics Researcher Profile Recognised Researcher (R2) Established Researcher (R3
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30 Jan 2026 Job Information Organisation/Company AALTO UNIVERSITY Research Field Management sciences Computer science Mathematics Researcher Profile Recognised Researcher (R2) First Stage Researcher
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Finland. Applications are welcome from all areas of operations research, including but not limited to optimization, mathematical programming, analytics, data-driven decision-making, stochastic modelling
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
for predictive modelling and state estimation for fundamental applications within physical sciences. Your role The main research responsibilities involve building cutting edge machine learning techniques