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monitoring and prediction using digital imaging, machine learning, and predictive modeling Collaborate with interdisciplinary teams for the design and development of high-performance materials with enhanced
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), Potentiodynamic Polarization, and Scanning Electrochemical Microscopy (SECM) Corrosion monitoring and prediction using digital imaging, machine learning, and predictive modeling Collaborate with interdisciplinary
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multilayer networks. Since multidimensional networks can be represented by tensors, one can think of applying tensor completion methods which have proved to be efficient in many applications such as image and
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which have proved to be efficient in many applications such as image and video reconstruction. However, the same issue arises, tensor completion methods can not be directly applied to recover the links
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-IoT system/network considering communication and data fusion requirements. Conduct a theoretical analysis of the developed designs. Develop simulations (writing code) to support the theoretical findings
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numerical modeling and simulation tools such as COMSOL, ANSYS Fluent, or particle-in-cell (PIC) codes for plasma dynamics and chemical kinetics A commitment to pedagogical innovation and the ability to mentor
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entities is highly desirable. Finally, the candidate should demonstrate good address for meeting and conferring with others, and potential for academic and scientific leadership. Strong skills in coding
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potential for academic and scientific leadership. Strong skills in coding using R, Python and Matlab will be a plus. The successful candidate will contribute to building a solid research portfolio at
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(teaching assistant or instructor roles may be sufficient) Familiarity with numerical modeling and simulation tools such as COMSOL, ANSYS Fluent, or particle-in-cell (PIC) codes for plasma dynamics and