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Field
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preparation protocol optimized for low-quality DNA extracted from fuel samples. The initial appointment is for three months, with potential for extension based on funding availability. Key Responsibilities
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, incorporating electronic, thermo-fluid models, and efficiency models (ii) BMS-BTMS operation policy design, which will be based on optimal control techniques and will focus on both electric power
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the NRF CREATE programme Singapore Aquaculture Solution Centre (SAS-C). This position is tailored for candidates with expertise in visual signal processing, biosignal interpretation, growth monitoring, and
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, or a related field Extensive experience in the controllable synthesis of nanomaterials. Expertise in machine learning-assisted materials design and process optimization. Expertise in
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that can be designed and optimised for both passive and active photonic components, allowing for the full suite of device functionality to be incorporated via simple and low-cost processes on a single
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other associates to develop optimized photonic test structures that will be incorporated in PIC process flows and enable extraction of key physical parameters associated with PIC performance, including
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optimization of multi-modal LLMs. Investigate and implement methodologies to ensure AI authenticity, accountability, and the integrity of digital content. Develop and refine machine learning and deep learning
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/experimentation. • Design and develop an intelligent and optimal switching strategies, control techniques, and energy management system (EMS) for the energy efficient and reliable operation. • Perform HIL
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Requirements: PhD degree in Electrical Engineering or related subjects. Expert knowledge in power system modeling and simulation. Research experience with power system operation and optimization. Excellent
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optimizing fabrication and testing processes for new devices. Qualifications PhD degree in Electrical Engineering, Materials Science, Mechanical Engineering, Biomedical Engineering, or a related field with