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), MEng/MSc (Research Associate) in Electrical Engineering, Computer Science, Statistics, or other related fields. Solid Mathematical skills. Experience in one of the programming language – Python, Matlab
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Employee Assistance Program For more information check out our benefits page! Your new team - "The School of Agriculture, Food and Ecosystem Sciences" The School of Agriculture, Food and Ecosystem Sciences
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PhD Research Fellow in Experimental Fluid Mechanics: Tunable hairy surfaces for droplet flow control
biophysics and sustainability thinking Follow our PhD program that include an educational component This is the right position if you are highly motivated about fundamental science and excited about questions
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Natural Sciences. The application to the PhD programme must be submitted to the department no later than two months after taking up the position. For more information see: http://www.uio.no/english/research
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a leading Employee Assistance Program For more information check out our benefits page! Your new team - "The School of Agriculture, Food and Ecosystem Sciences" The School of Agriculture, Food and
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-fields mentioned above. The successful candidate will be part of the Faculty’s PhD programme. The work is expected to lead to a PhD in political science. Required qualifications Formal qualifications
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U.S.C. § 272(b) and (c) Purpose: The National Institute for Standards and Technology (NIST) hosts the Professional Research Experience Program (PREP) which is designed to provide valuable laboratory
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community. Requirement: PhD in computer science/ engineering or related fields. Proficiency in Python is a must. Experience with other programming languages such as Java, C/C++, or Go, and frameworks like
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appointee will join the LEO Dr. David P. Chan Institute of Data Science and will be expected to: (i) carry out research and submit papers to top journals in the field of large vision models or large language
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interpretation and strain performance analysis. Automation and Computational Skills: Experience in implementing automation protocols for microbial strain engineering; Working knowledge of statistical analysis