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Field
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mission is to innovate with industry, through an integrated applied learning and research approach, so as to contribute to the economy and society. Singapore is the small city with a big dream. We are home
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with physical objects/environments, and audio rather than video based AR can help enhance memory/learning Humanizing Computer Mediated Communication: Synthesizing co-presence - What does it mean to feel
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or machine learning to complex data. The successful candidate will have (or be nearing completion of) a PhD in a relevant field such as polymer science, materials engineering, or mechanical engineering
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requirements: PhD degree in Computer Science, Electrical and Electronic Engineering, or related field. At least 3 years of relevant experience in computer vision, artificial intelligence, etc. Proficiency in
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into operational use cases. Prepare data collection frameworks and work on fish health monitoring datasets for machine learning training and benchmarking. Support the development of translational “lab-on-farm
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will conduct the lab experiment for RAS system for pollution control in recycled water in aquaculture system. He/she will also use machine learning tools to predict and optimize the RAS system. Job
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an opportunity for a Postdoctoral Fellow. You will contribute to UNSW’s research efforts in developing machine learning algorithm for photovoltaic applications and utilising them for the investigation
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, and semi-structured interviews. Using European competence models (e.g., GreenComp, LifeComp), the project will develop flexible lifelong learning models that universities can adapt to different
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relevant data science and machine learning tools. Able to work independently and comfortably with a team and external/international collaborators. Able to handle multiple tasks relevant to both project and
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in this position will conduct/lead applied as well as fundamental research in physics-informed Artificial Intelligence (AI) and Machine Learning (ML) methodologies enabling digital twin functionalities