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of field campaigns, data collection and lab work, Spectral data analysis, data processing, and model development, ‘R’, Python programming / package development, Co-supervise PhD and undergraduate students
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, including legumes, cereals, grasses, and vegetables. The appointed candidate will conduct field, greenhouse, and laboratory trials, analyze data, and publish findings in high-impact journals. The role
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system, network, and signal designs. Consequently, the project's main objective is to jointly consider communication and data fusion requirements in designing an efficient WSN-IoT system/network
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calculations to model and optimize heterogeneous catalysts. Conduct simulations to evaluate catalytic performance and reaction mechanisms. Analyze and interpret computational data to understand the interactions
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development. Proficiency in biodiversity monitoring tools and plant growth tracking. Field experimentation skills and experience in ecological data collection and analysis. Demonstrated hands-on experience
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data. Knowledge of computer-aided synthesis planning (CASP) tools and retrosynthetic analysis software (e.g., AiZynthFinder, ASKCOS, IBM RXN). Familiarity with reaction condition prediction and reaction
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Intelligence, Machine Learning, Data Science, Electrical Engineering, or a related field. Strong experience in developing and applying AI/ML models to energy systems or similar applications. Proficiency in
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partners and microbiome researchers to integrate multi-omics data for comprehensive resistome analysis. Publish high-quality research articles and present findings at international conferences. Contribute
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projects Keep the project team apprised about relevant information, progress and results of research activities, and clarify any issues in the implementation of projects/experiments in a timely manner as
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microbiomes and interpret the data using bioinformatics tools. Collaborate with interdisciplinary teams of researchers, including soil scientists, biochemists, and ecologists. Publish research findings in peer