119 parallel-processing-bioinformatics Fellowship positions at Nanyang Technological University in Singapore
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electrical engineering, computer science, computer engineering, social science or any other related fields. A strong track record of high-quality research in formal method based robotic operational
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to laboratory operation for the project. Job Requirements: PhD degree in physics, mathematics, engineering or related field Strong background in in photonics as well as in the use of electron sources, such as DC
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undergraduate students. Provide logistical support pertaining to laboratory operation for the project. Job Requirements: PhD degree in physics, mathematics, engineering or related field Strong background in
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-injection techniques, solvothermal/hydrothermal growth, and sol-gel processes. Expertise in semiconductor material characterization (XRD, SEM, TEM, EQE, PL, UV-Vis spectroscopy). Knowledge and experience in
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, Julia. Understanding of one or more of the following areas would be an advantage Optimization Dynamic systems Control theory Power electronics Signal processing Machine learning and data science (various
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factors and processes linked to students’ peer relationships, such as family and school climate and structures. For the first year of the Project 3, the main goals are to explore the nature and structure
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discovery and energy applications. The role involves investigating the electronic structure and surface properties of energy-related materials, with a focus on catalytic interfaces, adsorption processes, and
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. Job Requirements: PhD in Electrical and Electronic Engineering, Computer Engineering / Science, or related field Expertise in robotic system Familiar with ROS1 / ROS2 Good publication track record is an
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. Collaborate with a multidisciplinary team to ensure seamless operation of perception and control systems. Conduct experiments in real-world and simulated environments, with a focus on high-speed performance
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processing would be an advantage. Proficiency in statistical software (e.g., R, Python, SAS, or Stata). Experience with clinical informatics approaches (e.g., cluster analysis, machine learning, Bayesian