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work with hands-on offloading algorithm design and development for IoT networks. The core responsibility is to build and validate edge-assisted offloading strategies, complete with software APIs, through
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Punggol campus. Under this job title, you will be required to establish a test bed in SIT’s Punggol campus building, benchmarking of current building energy performances, deployment of new sensors
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edge-assisted offloading strategies for IoT networks. The role will bridge rigorous theoretical work with hands-on offloading algorithm design and development for IoT networks. The core responsibility is
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proteins, upcycled ingredients); AI and automation in food manufacturing - smart sensors, digital twins, and AI-driven food quality control and processing; Food safety - supply chain tracking/monitoring
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sensors, digital twins, and AI-driven food quality control and processing; Food safety - supply chain tracking/monitoring, blockchain Biotechnology: Host strain screening and engineering for microbial
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toxic gases emissions of various types of batteries potentially deployed in eHC through reduced scale testing. Lastly, you will also need to evaluate the various gas monitoring sensors performance in
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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eHC through reduced scale testing. Lastly, you will also need to evaluate the various gas monitoring sensors performance in detecting the battery gas releases for remote monitoring and early detection
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operation of the umFm module unit used in vertical farm which includes handling of soil compost, irrigating of the crops and taking note of the sensors incorporation in the vertical farm inhouse. Job