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implementing advanced hardware architectures and system-level solutions for next-generation computing, with a focus on memory-centric acceleration. Key Responsibilities: Design and develop Processing-in-Memory
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platforms for diabetes and extracellular vesicles research. Responsibilities include microfluidics engineering, cell culture, processing biofluid (e.g. blood) samples and data analysis/reporting, grant
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computer science, Computer Engineering, Electrical & Electronic Engineering, or related disciplines; A strong research background and publication record in relevant areas such as LLMs, agentic AI, Digital Twin
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digital transformation, perform tasks needed to bridge business users with CITS in the designing and implementing of solutions that improve NTU work processes. This position will partner closely with
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, Computer Engineering, or a related field. Strong background in smart contract security, blockchain systems, or software security. Experience in program analysis, formal methods, or vulnerability detection
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evaluation of the project’s core technical components in expert-in-the-loop agentic AI for manufacturing. Develop process-centric AI methods and software tools for BPMN modelling, Petri/CPN formalisation
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results in top-tier journals and conferences Job Requirements: Bachelor’s degree in electrical or computer engineering or computer science Good publication record with papers accepted/published in top-tier
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presentation works such as high-quality paper writing. Job Requirements: Preferably Master in computer engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical
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model training and finetuning. Job Requirements: Preferably Master in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical, proactive and a team
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the process of writing and publishing research papers in top-tier conferences and journals. Support the research team in documentation and reporting activities for the grant agency. Job Requirements: Preferably