390 web-programmer-developer-"https:"-"UCL"-"CNRS-" "https:" Fellowship positions in Singapore
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to Clinic & Pedagogy, Empowering Practitioners: Developing precision assessment and intervention tools to optimise parent-child social and mental health within clinical, education and community settings; 3
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topics and research tools. Responsibilities: Design, implement and lead research projects under CWP’s and IES’ research programmes Prepare high quality research papers on topics related to CWP’s core
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development opportunities through NUS events, seminars, and training programmes. Staff members also have opportunities to participate in regional and international academic engagements, including conferences
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related academic events. CIL provides its research staff with extensive professional development opportunities through NUS events, seminars, and training programmes. Staff members also have opportunities
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for a talented and motivated postdoctoral fellow to join the Genome Re-InnovaTion Lab (https://grit-lab.org), part of the Synthetic Biology Translational Research Programme at the National University
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with possibility of renewal of one additional year Start date: 1st Dec 2025, or as soon as possible The postdoctoral researcher will be expected to collaborate on existing lab projects and develop new
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for online education, team collaboration, and workplace training with a focus on real-time interactive simulation. (app developer) Design, build, and implement a multiplayer architecture and backend services
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international work environment Learn more about CQT at https://www.cqt.sg/ Job Description The Centre for Quantum Technologies (CQT), National University of Singapore is looking for researchers and engineers
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distributed energy resources (DERs). Design & develop optimization algorithms/tools to plan the deployment of DERs such as energy storage systems (ESS), photovoltaic generations (PV), electric vehicle charging
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by ARPES, pursue scalable wafer-scale moiré epitaxy, develop epitaxial superconductors for quantum computing and integrate machine learning for automated high-throughput MBE. We are particularly