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ELISA, immunoassays, electrochemical sensors, and/or mass spectrometry. Solid understanding of biochemical principles relevant to disease biomarkers. Preferable hands-on experience with patient sample
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Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience-informed design
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the development of a Virtual Training Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and
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for Science & Technology (KAIST), and an external stay at KAIST will be included as part of the PhD program. Qualifications Proficiency with Python Experience implementing various Machine Learning algorithms
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experimentation with Asst. Prof. Eli N. Weinstein. Your goal will be to develop fundamental algorithmic techniques to overcome critical bottlenecks on data scale and quality, enabling scientists to gather vastly
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et al (2015). A hybrid metaheuristic algorithm for the multi-depot covering tour vehicle routing problem. European Journal of Operational Research.
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Virtual Training Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience
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Virtual Training Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience
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architectures, and demonstration of showcase applications, like light emitters, light sensors, supercapacitors, and batteries. Research and training tasks will be carried out by a collaborative and
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, Materials Science, Chemical Engineering, Nanotechnology, or related fields. Proven experience in one or more of the following areas: o Electrochemical sensors and devices o Energy storage/conversion systems