10 distributed-algorithm Fellowship positions at SINGAPORE INSTITUTE OF TECHNOLOGY (SIT) in United Kingdom
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responsibility of this role is to deliver on an industry innovation research project where you will be part of the research team to design, develop and evaluate schemes for quantum key distribution networks and
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. The role will bridge rigorous theoretical work with hands-on offloading algorithm design and development. The core responsibility is to build and validate these offloading strategies, complete with Python
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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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Responsibilities Participate in the research project to design a microgrid controller for grid interactive building applications. Develop control algorithms for dynamic master selection, coordinating BESS, PV
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to the design, modelling, simulation, validation, and optimization of electric vessel power systems, with strong emphasis on battery-based propulsion, onboard microgrids, EMS algorithms, and real-time validation
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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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, advanced sensing techniques, sensor and operational data fusion, data analytics, and machine learning algorithms for condition monitoring, fault diagnosis, and early fault prediction in electric vessels
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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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external AI systems. Experience with distributed systems, reinforcement learning, or simulation environments (e.g., Unity3D, OpenAI Gym, WebGL) is advantageous. Experience in developing and deploying cloud
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learning. Familiarity with reinforcement learning (RL) principles, curriculum learning strategies, and the challenges of real-time systems. Working knowledge of distributed systems and container technologies