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be involved in the three-year project “High Dimensional Hierarchical Optimization methods for Machine Learning and Stochastic Optimal Control”. Background or expertise in one or more of the following
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develop phase-field and finite element models and work closely with experimental efforts at KAUST. Research areas include: Phase-field modeling of fracture Multiphysics coupling Finite element methods
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Applicants must have a PhD in Computer Engineering, Computer Science, or Electrical and Computer Engineering, and have published their research in prestigious conferences and journals in related
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optical, electronic, and photodetector properties. Responsibilities Synthesize III–V CQDs using air-free colloidal methods. Design and optimize precursor chemistry for InAs-, InSb-, Ag₂Te-, and PbSe/PbS
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on the development of new methods integrating a variety of data types (remote sensing, geology, geophysics, geochemistry) for geological modelling and advanced exploration targeting of mineral deposits
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analytical many-body methods, field theory, and/or numerical techniques is a plus. Details: For salary and program details see KFUPM’s Postdoctoral Research Fellowship Program page (link below). https
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integration methods for the different data types. In terms of applications, the candidate will be free to choose their own case study(s). Additionally, close collaboration with other group members is expected
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technologies. Key Responsibilities: Develop and optimize hard carbon synthesis processes using bio-based and non-bio-based precursors. Explore innovative methods to enhance material properties for energy storage
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-based precursors. · Explore innovative methods to enhance material properties for energy storage applications and other emerging technologies. · Conduct detailed structural, chemical, and