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, and academic oversight of AI-related programs targeting professionals, executives, and students across diverse learning stages. Working closely with faculty, institutional partners, and external
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are in particular targeting development of data-driven high-performance computing techniques for unbiased discovery of generative models & theory and algorithms for network inference with special reference
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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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in the design, processing, and characterization of advanced semiconductors — including organic, hybrid, and 2D materials. Applicants should demonstrate a strong track record of fundamental and applied
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and strategic partnerships. Essential Qualifications: Ph.D. degree obtained within the last 2-3 years, and possessing a strong track record of research excellence. Candidates nearing completion
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be considered. Successful candidates should hold a Ph.D. in Biological Sciences or a related field, with a robust track record of publications in top-tier journals, and must be eager to pioneer