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alarm protocols; experience in sensor deployment/SCADA and data processing. Ability to optimize regeneration systems and integrate them into service networks; knowledge of EU regulations on water reuse
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Polarization (PHIP). Experience in NMR and MRI pulse sequence development, optimization, and implementation. Strong quantitative and analytical skills for processing and modeling magnetic resonance data
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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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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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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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, fluorescence screening, RNA footprinting and computational methods to study the atomic structure and dynamics of the RRE, identify new antiviral candidates and guide the optimization process. The publication
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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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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