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Field
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validation and Pileup modeling), the MET High-Level Trigger validation, optimization and performance studies, and to the heterogeneous computing where the focus will be to work on to the current efforts
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of species, including horses, cattle, pigs, rats, mice, sheep, and birds and to extend efforts at optimizing performance and health in humans and livestock. • Assist with writing grant proposals, manuscripts
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into the same devices. The research project is part of a larger consortium, gathering world-class researchers in remote sensing with expertise ranging from estimation and optimization theory to hardware design
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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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to optimize their durability and efficiency under industrial conditions. The goal is to contribute to a sustainable energy storage solution while avoiding the use of expensive metals. The postdoctoral
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optimization and Al tools to coordinate and optimize the role of ESS within the onboard microgrid. This project finds it context in the urgent need to reduce greenhouse gas émissions and improve the energy
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optimization of optical imaging hardware, develop data acquisition software and algorithms for data processing, as well as perform phantom and human clinical studies. This candidate is expected to co-supervise
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machine learning models (e.g., VAEs, GANs, transformer-based models) to large-scale biomedical and biological data, including developing and optimizing models to predict disease progression and create
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physiology and adaptation for industrial applications; high-throughput screening and automation for strain optimization; bioprospecting for novel microbial hosts, enzymes, and metabolites to support
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future data management / governance approaches. Aim is to optimize the shared service model enabled by improved data sharing, deployment of digital technologies and redesigned workflows. With this project