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research. The ability and willingness to adapt and incorporate novel ideas and approaches in scientific industry. Demonstrated ability to formulate hypothesis and design effective experimental plans. Ability
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manufacturing Definition of appropriate material stacks, materials and processes products from chemical and mechanical aspects Chemical characterization of materials within component specifications Chemical
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The School of Materials Science and Engineering (MSE) provides a vibrant and nurturing environment for staff and students to carry out inter-disciplinary research in key areas such as Computational
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the creation of robust early warning and stress classification pipelines in close collaboration with fish farming industry R&D. This role complements ongoing work in AI-based decision-making and is ideal
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research on design and manufacturing of soft fluidic catheter robotics. This role will propose novel design of soft robotic materials and structures driven by the fluidic environment. Experiments will be
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innovative research. The ability and willingness to adapt and incorporate novel ideas and approaches in scientific industry. Demonstrated ability to formulate hypothesis and design effective experimental plans
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for a fast and thorough transfer of research output into the industry. SHARE at NTU aims to expand the current state of technology and build on Robotics & Industry 4.0 as aligned with Schaeffler’s
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of faculty, students and alumni who are shaping the future of AI, Data Science and Computing. We are seeking a research fellow to join a university-level research centre collaborating with industry
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conferences, presenting results to stakeholders and industry experts. Job Requirements: Ph.D. in electrical engineering, computer science, or a related field, with a strong background in AI/ML, wireless
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and federate learning. Collaborate with Centre’s engineers and industry partners to develop and implement proposed research solution. Prepare high-quality research publications and contribute to report