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cryosphere and is involved in various high-level research projects and centers. (See for instance http://www.mn.uio.no/geo/english/about/organisation/geohyd and https://www.mn.uio.no/geo/english/research
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research projects and centers. (See for instance http://www.mn.uio.no/geo/english/about/organisation/geohyd and https://www.mn.uio.no/geo/english/research/groups/remotesensing ). We are a growing, lively
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Computational Postdoctoral Fellow (Quantitative Modeling Group) - 106785 Division: BE-Biological Systems & Engineering Berkeley Lab’s (LBNL, https://www.lbl.gov/) Biological Systems and Engineering
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areas: i. Advanced welding and automation technologies for steel fabrication and construction ii. Experimental investigation of high-strength aluminium alloy structures iii. Development and testing
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and apply advanced methods in automated treatment planning, artificial intelligence, adaptive treatment delivery, and clinical workflow optimization to improve both the quality and efficiency
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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
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Nordic, or boreal forest ecosystems Demonstrated experience in field-based forest experiments and development of environmental monitoring systems using automated data acquisition and microcontroller-based
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automation. Evaluate monitoring and centralized management methodologies, measuring gains in operational efficiency and assessing the robustness of the implemented topology against failures and service latency
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are encouraged to also articulate how their research will leverage or advance AI, advanced computing, data, automation, and other emerging capabilities to accelerate discovery and impact within these priority
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Materials, Bioinspired Materials and Sustainable Materials. For more details, please view https://www.ntu.edu.sg/mse/research . We are looking for a hands-on Research Fellow whose role will focus