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Field
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discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials. Candidates who are nearing completion
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nonproliferation. With guidance, the appointee will : Develop advanced multiscale, multiphysics simulation tools relevant to the modeling of processes involving combined nuclear, chemical, and electrochemical
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correction, or many-body quantum systems. o Proficiency in numerical simulations (e.g., tensor networks, quantum circuit modeling). · For Experimentalists: o PhD in atomic/molecular/optical (AMO) physics
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: Develop data-driven numerical models (opinion models, norm dynamics, multi-agent systems). Network Science: Study social and temporal interaction networks using network physics tools. Simulation: Conduct
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on pay scale group 13 of the collective agreement for the public service of the German states (TV-L). Your role While much current AI research focuses on large generative models, our group aims to explore
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related field in hand by May 2026. Preferred Qualifications: Experience in Thermal Spray Materials/Processes/Characterization/Modeling. Experience in Solid Mechanics/Thermomechanics/Finite Element Analysis
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. The candidate will reduce model uncertainties by producing new large cosmological simulations of the magnetic outputs from galaxies in the ENZO code, which will test realistic implementations of baryonic feedback
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modeling and characterization for communication and sensing in emerging spectrum for 6G and beyond, with a focus on the FR3, THz and optical frequency bands. This research will be conducted under the joint
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and novel device technologies Develop, validate, and maintain simulation and modeling frameworks for detector performance, characterization, and benchmarking Analyze simulation results and experimental
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rare-earth ions, with improved quality for optical, magneto-optical and laser applications. Different growth methods will be used such as Czochralski, Bridgman and Flux methods. Numerical modelling will