18 mosquito-behaviour Fellowship research jobs at Singapore Institute of Technology in Singapore
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: FEM Modelling: Utilise FEM software (Ansys/ABAQUS) to design the floating breakwater to ensure structural robustness CFD/BEM Modelling: Utilise CFD software (Star CCM/Fluent) to study the wave behaviour
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on emerging threats and operational feedback. Conduct pilot testing on 5G testbed to monitor their effectiveness in real-time applications, followed by comprehensive evaluation and validation to ensure
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technology. Key Responsibilities: Collaborate with partners from both the academia and the industry to lead and/or conduct innovative research on, but not limited to transfer learning, explainable machine
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industry partners. Key Responsibilities Integrate network slice-based firewall policy, focusing on behavior of the slice to enhance End-to-End (E2E) security. Implement and test a feedback system to
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production, oral processing characterization and conduct of surveys. The position requires a strong background in food chemistry, food product development, colloidal science, sensory science as well as survey
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. Lead and conduct bench-top and pilot plant food processing involving extrusion to produce samples, with the support of the team members. v. Plan, organize and carry out experiments and trials in the food
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members to ensure all project deliverables are met. Undertake these responsibilities in the project: i. Lead and conduct bench-top and pilot plant extraction process for sustainable food ingredients and
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these key responsibilities in the project: Design appropriate mechanical tests that relate to food break down in the mouth Conduct materials testing to characterise the mechanical behaviour of the foods
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and beyond. The work package WP2.2 in FSSD will conduct the research in the areas of design FMECA, functional FMECA, advanced sensing techniques, sensor and operation data fusion, data analytics and
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the industry to lead and/or conduct innovative research on, but not limited to evolutionary computing, job scheduling, transfer optimization, transfer learning, reinforcement learning, large-scale