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Field
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for postdoctoral fellowships in computer science with emphasis on the area of formal methods, in connection with topics that include (but are not limited to) computational complexity, distributed systems, human
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distribution: 50%: Laboratory work involving modern polymer characterization. Maintaining lab equipment. Manifest chemical waste. Troubleshoot instrumentation. Work with undergraduate, graduate, and postdoctoral
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package to our employees. Benefits eligibility is subject to employment status, full-time equivalent (FTE) workload, and weekly standard hours. Please visit our website at https://hr.wustl.edu/benefits
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standard hours. Please visit our website at https://hr.wustl.edu/benefits/ to view a summary of benefits. EEO Statement Washington University in St. Louis is committed to the principles and practices
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annual budget of over € 5 billion, the Helmholtz Association is Germany's largest scientific organisation. Where to apply E-mail [email protected] Website https://gfz.concludis.de/prj/shw
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
31 Jul 2026 Job Information Organisation/Company Inria, the French national research institute for the digital sciences Research Field Computer science Researcher Profile Recognised Researcher (R2
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, you may refer to https://www.uni.lu/snt-en/research-groups/sigcom/ . Your role The successful candidate is expected to assume a key role in experimental quantum communications and networking, in
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well as microfabrication technologies, is desirable. A good level of written and spoken English is required. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR7252-AURCRU-006/Default.aspx Work Location
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application form is available through IBEC dedicated site: https://careers.ibecbarcelona.eu/ Only those applications submitted before the deadline will be evaluated. Reference: Phd-SS If you have any further
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environments. Clean public repositories or released source code from past publications is a strong plus. Algorithmic Breadth: Familiarity with probabilistic machine learning, distributional reinforcement