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-on experience in optimizing extraction processes and characterizing bioactive ingredients from various biomass. Demonstrated competence in purification/isolation and structure elucidation of pure natural products
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applications for a Postdoctoral Fellow position in the field of green flotation chemistry and sustainable mineral processing. This research project focuses on the development, characterization, and application
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interpretation of remote sensing data, allowing for rapid decision-making in critical situations, such as during natural disasters. AI models can process big datasets efficiently, helping to make informed
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multispectral/hyperspectral data processing. Proficiency in programming languages such as Python or R for data analysis and processing. Excellent communication skills and the ability to work effectively in a
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field. Strong background in machine learning, particularly deep learning and natural language processing. Experience with transformer-based architectures (e.g., BERT, GPT) is highly desirable. Proficiency
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university, with its state-of-the-art campus and infrastructure, has woven a sound academic and research network, and its recruitment process is seeking high quality academics and professionals in order to
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recently completed (or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically LLMs
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sustainable mineral processing. This research project focuses on the development, characterization, and application of bio-based flotation additives to improve the enrichment and beneficiation of phosphate ores
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, Cosmetology, Natural Products Chemistry, and Cell biology or related field. Requirement Hands-on experience in optimizing extraction processes and characterizing bioactive ingredients from various biomass
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activities. Qualifications: Ph.D. in Bioinformatics, Computational Biology, Computer Science, Genomics, or a related field. Strong background in machine learning, particularly deep learning and natural language