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Field
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Mission: Carry out tasks of the H-HOPE research project assigned to the IFLUIDS research group. Functions to be developed: Analyze pilot data and numerical simulation of the systems developed with
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environments. Working closely with partners in the NEXPECH₂ project, you will analyze their materials and provide valuable insights to help optimize device performance. Additionally, you will support
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of digital data in DNA. -Contribute to designing and optimizing methods for DNA digital data storage in nanomaterials. -Collaborate with interdisciplinary teams, including molecular biologists, chemists
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innovative experiments. The work will include defining and optimizing in vitro models using diverse cell types and advanced platforms, as well as establishing correlations between applied mechanical stimuli
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valuable insights to help optimize device performance. Additionally, you will support collaborators by assisting with in-situ TEM measurements, facilitating cutting-edge research in sustainability and energy
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be clinically tested in a small animal model. (Ref: PID2022-136961NB-I00)(HR25-00225). Main functions: Design, fabrication, and optimization of liquid-walled pumps (Qpump) capable of achieving
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environments, specifically Computer Vision, Machine learning algorithms and methods for rock characterization, fragmentation prediction, and mining optimization. Specific Requirements Good academic and
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biology, chemistry and virology laboratories at Catholic University of Valencia, University of Barcelona and the IrsiCaixa and ISCIII research institutes in Spain will use state-of-the-art in vitro and in
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Leonardo. The successful candidate will play a crucial role in developing and optimizing machine learning workflows for large-scale environmental data analysis, contributing to the creation of robust and
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interface between ESM and the latest version of SIESTA, its validation, its benchmarking, and its exploitation in scientific applications. Work will also involve the optimization of SIESTA on the fastest and