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Field
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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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/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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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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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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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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optimization, and covalent drug design. Collaborating with researchers and engineers at the Monash Institute of Pharmaceutical Sciences and QDX Technologies to implement scalable AI–quantum hybrid platforms
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the following tasks: Development of new large language models for process modeling Development of new decision-making algorithms Provide regular project updates to principal investigator and funding agency Report
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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
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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
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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