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on hyperspectral imaging data acquired from cultural heritage objects. The postdoctoral researcher will conduct research aimed at developing and implementing hybrid models that combine physical radiative transfer
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Antarctica Ice Sheet. By combining high-resolution chemical mapping with detailed microstructural analyses—encompassing crystal shape and orientation, as well as bubble size and distribution—across basal ice
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. Using all-atom molecular dynamics simulations and enhanced sampling techniques, the project will investigate how S-glutathionylation modulates nucleosome structure and dynamics, alone and in combination
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representative microstructures or using an equivalent homogenized material model. The project therefore combines multi-scale modeling, large deformations, nonlinear viscoelasticity, and transient dynamics
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:this project pioneers a new paradigm of General Genome Interpretation (GenGI) models by combining DNA Large Language Models (DLLMs) with Deep Neural Networks to predict human phenotypes directly from Whole Exome
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approach, Timelapse-Patch-Seq (TiPS), combining electrophysiology, 3D imaging and transcriptomics at the level of individual synapses. Main tasks Design and conduct a postdoctoral research project on long
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and conversion. The integrated team is renowned for its research in photovoltaics and photocatalysis, combining fundamental science with applications such as green hydrogen production and biomass
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combine density functional theory (DFT), molecular simulations, and machine-learning force field (ML-FF) development to uncover the factors controlling NHC–surface interactions and to model realistic
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substrate effects using a combination of TB-SMA and Tersoff potentials. Perform atomistic simulations (molecular dynamics and Monte Carlo) to generate diverse and realistic structural configurations
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approaches combining ab initio modeling, Raman vibrational spectroscopy, and machine learning for the study of electrode materials and their interfaces, with a focus on operando monitoring of full battery