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systems to support end-to-end autonomous operation. Build and maintain simulation environments, multimodal datasets, and evaluation frameworks, handling data volumes from tens to hundreds of gigabytes
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engineering or related field At least 1 year of relevant experience in signal processing and machine learning. Good written and oral communication skills Proficiency in ANSYS, and lab test skill Ability to work
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operation of research lab equipment and robotic systems. Job Requirements: Master’s degree or Bachelor’s with top-tier conference paper (mandatory) in Computer Science, Robotics, Mechanical Engineering
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processing of required PLC waveforms and perform rigorous EMC/EMI tests for compliance. Prepare technical reports and present progress to lab stakeholders and industry partners. Job Requirements: PhD degree in
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operational processes for the programmes. You will also be key in designing the professional and social events that form an integral part of the programme experience for the participants. Key Responsibilities 1
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of processes and implement automated solutions where feasible. Utilize AI-driven insights to monitor project performance and identify areas for improvement before they impact the user community. Requirements A
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ensure data integrity and accuracy, addressing any discrepancies proactively. Collaborate with the Development team to enhance the efficiency of processes and implement automated solutions where feasible
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like NLP, Computer Vision, or on tabular data. Generative AI & LLMs: Hands-on experience developing LLM-powered applications, including Prompt Engineering, Retrieval-Augmented Generation (RAG), and fine
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. Assist in general operation of laboratory including ordering supplies and maintenance Train new laboratory personnel, students, and short-term visiting scientists Comply with all laboratory safety
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related field. Strong interest or experience in data analysis and time-series modeling. Proficiency in Python for data processing and model development. Basic knowledge of machine learning or deep learning