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Field
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
Dhabi seeks to recruit a highly motivated Post-Doctoral Associate to work on topics in the theoretical foundations of data science and AI. Responsibilities: Conduct research on automated reasoning and
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position within a Research Infrastructure? No Offer Description Applications are invited for a temporary post of a UCD Post-doctoral Research Fellow Level 1 in Microalgal Carbon Capture and Automation
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Science, Materials Engineering, Nanotechnology or related fields Desirable requirements: Post-Doctoral position #1 – Experience in high-pressure reactors, pilot plants, process automation, instrumentation
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. Responsibilities: Conduct research on automated reasoning and proof checker, AI-assisted collaboration. Develop and analyze algorithms for learning and optimization. Participate in collaborative research projects
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rural Michigan communities have adapted to decades of workplace automation in manufacturing and agriculture. Working across three case counties, the postdoc will conduct sustained observational fieldwork
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carry out scientific studies in the area of smart and portable automation. The position will be conducted within the framework of the research profile MARC (Mälardalen Research and Competence Centre
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skills in English. Ability to work effectively in an international and multidisciplinary team. Experience with HHG sources, high-power laser systems, vacuum technology, XUV optics, detectors, automated
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of integrated photonic devices and systems, including automated measurement and control setups. Contribute to the development of novel photonic solutions for applications in quantum technologies, optical
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Job description The AICell Lab (https://aicell.io ) in the department of Applied Physics at KTH and
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well as exploring the application of research findings to advanced 3D models such as organoids and 3D bioprinted tissues Learning about high-content, automated phenotypic drug screening pipelines against high