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. Conduct comprehensive physical, chemical, and mineralogical characterizations utilizing techniques such as XRF, ICP-MS/OES, QEMSCAN, XRD, SEM, alongside standardized environmental tests such as ABA, NAG
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(e.g., using USIMPAC or similar software). Analyze, interpret, and report the outcomes of simulations and pilot tests. Draft technical reports and scientific publications. Coordinate with internal
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processes for virtual commissioning and optimization. Examine extensive heterogeneous data sets (including historical process data, sensor data, and laboratory findings) using advanced AI approaches such as
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either agronomic testing or material development, with willingness and ability to work across disciplines Experience in the development and characterization of glass materials and/or controlled-release
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/membrane testing instruments; Willingness to learn how to generate new ideas, links, and to build upon existing ideas to generate good concepts and solutions; Ability to co-supervise graduate students
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fertilizers. Demonstrated experience in either agronomic testing or material development, with willingness and ability to work across disciplines Experience in the development and characterization of glass
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testing, and advanced process simulation, with the objective of optimizing grinding performance and enhancing resource recovery. The ideal candidate will have a strong background in mineral processing
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of research and education, covering all aspects of computer science, including artificial intelligence, machine learning, data sciences, algorithms, databases, cloud computing, software engineering, networking
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, including artificial intelligence, machine learning, data sciences, algorithms, databases, cloud computing, software engineering, networking, operating systems and security. Job Description The successful
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terms of research and education, covering all aspects of computer science, including artificial intelligence, machine learning, data sciences, algorithms, databases, cloud computing, software engineering