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on the interactions between rhizosphere microbiota and plant roots, investigating how microbial enzymes enhance plant stress tolerance under salinity conditions. The successful candidate will: Conduct metaproteomic and
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, and suspension flows. A key objective is to link microscale interactions between bubbles, droplets, and particles with the macroscopic behavior of the system through a multiscale framework. Additionally
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groundbreaking mechanisms in electron-photon and electron-matter interaction, pertaining to the compact, efficient generation of extreme ultraviolet light for applications including EUV spectroscopy and EUV
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designs research for various stakeholders. Provide production support for visual communications including creating maps, diagrams, graphics, and renderings. 25% Program management support Track and document
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. Preference will be given to those with relevant research experience in collaborative generative AI, foundation models, multimodal AI or interactive intelligent systems. Applicants for the Research Associate
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, committed prospective plant and soil modellers to contribute to a multi-partner international project ‘Climate-resilient crops with improved phosphorous efficiency through beneficial fungal interactions
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interact collegially with individuals of different backgrounds Ability to work some evening hours Skill in graphic design software Preferred Qualifications Previous leadership position. Previous experience
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: Experience with R (data wrangling, visualization, statistical modelling) Experience with experimental methods (e.g., eye-tracking, EEG/ERP, self-paced reading, speech production) Experience working with
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phosphorous efficiency through beneficial fungal interactions’. About the Role In many parts of the world, excessive use of phosphorous (P) fertilisers in agricultural soil has led to large-scale contamination
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for drone swarms. The role will focus on multi-agent visual perception techniques. Group website: https://personal.ntu.edu.sg/wptay/ Key Responsibilities: Develop signal processing and machine learning