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genetics, cell biology, genomics, and bio-computing to unravel plant biological processes and to further translate this knowledge into value for society. Please visit us at www.psb.ugent.be for more
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) and computer simulation (FEA) Experience in material characterisation and experimental testings Knowledge in impact dynamics Passionate and have interest in pursuing PhD degree. Experience in research
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structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data analysis techniques, are preferred. Application process To apply
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global water contamination through advanced materials science. Your Role: Investigate the structural and chemical dynamics of molecular adsorption processes using advanced characterization techniques
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use by the group employ multiple-input multiple-output (MIMO) technology and can be connected to build a distributed and cooperative network. To develop signal processing techniques, the group
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Requirements: excellent university degree (master or comparable) in computer engineering or electrical engineering a strong background in digital design, hardware description languages (e.g. Verilog, VHDL
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publications and research experiences in structural dynamics and structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data
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are part of the programme. The research is funded by the Centre of Propulsion and Thermal Engineering at Cranfield University. The work will be conducted at the Cranfield icing wind tunnel (IWT) based
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of mathematical models to the development of new imaging-related techniques and compounds. The programme is searching for excellent students who hold a Master's degree in Biology (or related fields), Physics
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the growing demand for sustainable AI-enabled systems, this PhD brings together low-power computing, energy-aware design, and thermal optimisation. You’ll work with advanced profiling tools, prototype long-life