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Field
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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
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environment. The Functional Optoelectronic NanoMaterials group at ICFO, led by ICREA Prof. Gerasimos Konstantatos, is looking for outstanding, creative and highly motivated researchers to develop highly
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to) SIESTA (www.siesta-project.org) and its TranSIESTA functionality. SIESTA is a multipurpose first-principles method and program, based on Density Functional Theory, which can be used to describe the atomic
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conditions. Conducting mechanistic studies to determine the thermodynamics and kinetics of key reaction pathways, including deactivation processes. Screening and fine-tuning catalysts to enhance performance
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permit to work in Spain Experience & Skills • Strong background in Neurosciences or related fields • Certification in the “Training course for research personnel using experimental animals” or equivalent
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. The successful candidate will be joining the Quantum Optics Theory group led by Prof. Dr. Maciej Lewenstein. The successful candidate will work on Machine Learning research. Share this opening! Use the following
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detection, devices with advanced functionalities etc.) Many advanced tools will be available such as (dilution) cryostats with optical access, cryogenic scanning near-field microscope, optical quantum twist