19 algorithm-development-"Multiple"-"Simons-Foundation"-"Prof"-"UCL" uni jobs at Chalmers University of Technology
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systems. Our work spans the full development cycle, from quantum device design and nanofabrication to low-temperature characterization and quantum measurements. You will join the Quantum Computing Group
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-emitting vertical-cavity surface-emitting lasers (VCSELs), with expertise and infrastructure covering most aspects of VCSEL development — including design and simulation, laser fabrication, and material
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-14156 Is the Job related to staff position within a Research Infrastructure? No Offer Description This position creates an inclusive environment to closely work with the Swedish industry in developing
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This position creates an inclusive environment to closely work with the Swedish industry in developing methods and tools related to flow-induced acoustics, which is a critical aspect for modern
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Built Environments Research Area (Sustainable Building group) at the Department of Architecture and Civil Engineering . This research area focuses on developing methods, tools, and strategies to enhance
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photonics by developing and implementing experimental methods, maintaining and improving laboratory facilities, and collaborating closely with researchers, PhD students, and external partners. As a Research
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description We are looking for a Research Specialist to provide advanced technical and methodological support in integrated photonics by developing and implementing experimental methods, maintaining and
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pioneering research on rethinking space and municipal planning processes conducted in co-creation and a transdisciplinary setting spanning architecture, urban development, human geography, ecology, and economy
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of AI and materials science, addressing real-world challenges in thermal management for high-performance computing and 6G infrastructure. We offer: (1) You will develop marketable skills in AI, ML, and
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of surface sites makes theoretical understanding difficult. This project will develop and benchmark machine learning models to predict local electronic density of states (DOS) at alloy catalytic sites