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to the UrEco 2030+ project: “Optimizing Urban Ecosystem Services Model for Urban Climate and Biodiversity in Singapore towards 2030 and Beyond.” This position requires experience in Geographic Information
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Requirements PhD/Master’s in Naval Architecture, Ocean Engineering, Civil Engineering, or related field. Proficiency in hydrodynamic modeling tools (e.g., WAMIT, ANSYS AQWA, OrcaFlex) and finite element analysis
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Master’s or PhD degree in relevant areas will be advantageous. Familiarity with the following areas is advantageous: Participation in Kaggle competitions, showcasing practical problem-solving and model
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Fellow) PhD in Computer Science or a related field (Research Engineer) Bachelor/Master degree in Computer Science or a related field Proven ability to conduct independent research with a relevant
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or PhD degree will be advantageous Knowledge of physical modelling will be advantageous. Where to apply Website https://www.timeshighereducation.com/unijobs/listing/409590/research-engineer-g
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to the UrEco 2030+ project: “Optimizing Urban Ecosystem Services Model for Urban Climate and Biodiversity in Singapore towards 2030 and Beyond.” This position requires experience in Geographic Information
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mathmatical modeling. The candidate should also have a PhD or other advanced degree in a food or engineering related field. Knowledge of food formulation, sensory analysis, extrusion technology, machine
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the project: Develop, train, and optimise deep learning models for wildlife species identification, classification, and segmentation using real-world datasets. Design and implement software modules to integrate
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that are relevant to industry demands while working on research projects in SIT. The researcher will be part of the team of the CFI Project (https://www.pub.gov.sg/-/media/PUB/Resources/Press-Releases/2024/06/Annex
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available at all levels from Lecturer to Full Professor in Chemical Engineering or related disciplines. Priority skill areas include: process monitoring and control, industry 4.0, modeling, AI and ML