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functional materials. Research activities focus on controlled polymer synthesis, macromolecular engineering, polymer self-assembly, nanoparticle design, and the development of stimuli-responsive polymer
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experience in power electronics (10%) 2. Design and optimization of power supplies. (10%) 3. Modelling, design and optimization of high frequency magnetic components (25%) 4. Modelling and control of power
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Mission: Develop a monitoring and control system for an ammonia dehydrogenation plant. Functions to be developed: Perform plant modeling. Design an optimal control system. Design estimation algorithms
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ability to finish assignments on time. More information on Dr. Jin’s laboratory can be found at: http://pulmonary.medicine.ufl/about-us/meet-the-team/facultyarnpspas/lei-jin-phd-msc/. Laboratory Management
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generation of MOF water adsorbents with optimal indoor air humidity control performance by leveraging state-of- the-art high-throughput (HT) computational screening based on Machine-Learning Interatomic
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machine learning methods to extract meaning from data; building, managing, and optimizing ETL pipelines and SQL databases for research purposes; implementing linkages of large administrative datasets and
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Materials, Bioinspired Materials and Sustainable Materials. For more details, please view https://www.ntu.edu.sg/mse/research . We are looking for a hands-on Research Fellow whose role will focus
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of gene therapy manufacturing and process innovation. The project focuses on the development and optimization of scalable bioprocesses for viral vector production and downstream purification and
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Laboratory of Computer Science, Robotics and Microelectronics of Montpellier (LIRMM) and Alternative Energies and Atomic Energy Commission (CEA) | Montpellier, Languedoc Roussillon | France | 2 months ago
robotics and to develop a comprehensive methodology for the design, modeling, control, and experimental validation of frugal multi stable robots, from the elementary module to the assembled robot. The work
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(for example: optimization in machine learning, optimal control problems, optimization with partial or ordinary differential equations, parameter identification). We are particularly interested in areas