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combines approaches from computational physics, machine learning, neuroscience, and gene technology. The postdoc is expected to contribute to develop machine learning models for the construction
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of large and complex data sets, spanning brain imaging, genetics and clinical data. The goal is to reveal more of the genetic architecture underlying brain structure and function and to improve our
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, postdocs, PhD fellows, engineers, admin and master students. The research group has an excellent infrastructure covering chemical, structural, optical and electrical characterization methods, device
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-mental sustainability of the medium for hydrogen storage Structural and hydrogenation characterization of alloys, including their feasibility under realistic conditions envisioned for AtLAST The core
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. The overall goals of the present research are to provide new insights into the roles of the cerebral cortex and its connectivity with the thalamus in FND. We will include functional and structural brain
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, structural, optical and electrical characterization methods. Part of the research will be conducted at the Micro- and Nanotechnology Laboratory , with a clean room area more than 400 m2 as well as a park of
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capabilities and expertise in synthesis, advanced characterization, and modeling. The group also specializes in structural studies by using X-ray based operando methods. The battery activities at NAFUMA have
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-edge research focused on the simulation of spectroscopic properties to unravel the geometry and electronic structure of complex systems. Key areas of research include electronic spectra simulations (XPS
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learning models for the construction of constructs and capsids using combinations of discriminative and generative methods, methods for protein structure prediction and docking simulations. The successful
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, benefiting from a large herbarium collection. We will focus on The impact of structural variants in local adaptation; Pangenome approaches to detect variation in gene content across individuals; The position