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preparation for use in AI models; - Experience with explainability techniques for Machine Learning models; - Desirable experience with system modernization. To apply, send an email with the subject “Inscrição
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Previous Job Job Title Post-Doctoral Associate Next Job Apply for Job Job ID 372636 Location Twin Cities Job Family Academic Full/Part Time Full-Time Regular/Temporary Regular Job Code 9546 Employee
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 16 hours ago
Position Title Post-Doc Research Associate Vacancy ID PDS004788 Full-time/Part-time Full-Time Temporary Hours per week 40 FTE 1 Work Location Chapel Hill, NC Position Location North Carolina, US Hiring Range
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Postdoctoral Associate / Senior Postdoctoral Associate Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) PhD or MD or foreign equivalent in hand by date of hire
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adoption, real-world relevance, and a clear pathway from prototype to market deployment. Achievement of the expected progression within Post Doc and Senior Post Doc is transferable between the Irish HEI’s
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. The position bridges machine learning and molecular science, with opportunities for collaboration, mentorship, and impactful research. About us The Department of Computer Science and Engineering (CSE
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of nanodevices and their multiple functionalities for bio-inspired computing. The team includes two permanent CNRS researchers, two Thales researchers, 4 post-docs, and 4 PhD students. Where to apply Website https
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, stochastic differential equations, computational methods in fluid mechanics and turbulent flows, high-performance computing, machine learning methods in computational problems. GSSI is a world-renowned
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. Experience in high-throughput sequencing data analysis and cluster/cloud computing. Proficiency in variant calling, single-cell DNA and/or RNA analysis, and machine/deep learning (preferred but not required
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subsea digital twin of deep-water mooring lines for floating offshore wind turbines. The digital twin will be integrated with machine learning algorithms for detection of primary entanglement due