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. · Efficient algorithms for emulation of quantum computing and networking. · Developing and applying machine learning algorithms to optimize quantum computing and networking. · Quantum sensing
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Number: 6981301 Part-Time Lecturer- Khoury College of Computer Sciences- Seattle About the Opportunity The Khoury College of Computer Sciences invites applications for the position of Part-time teaching
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master’s degree with academic qualifications in digital health, data analysis, and/or machine learning applied to health research. Admission to the PhD program requires a 120 ECTS master’s degree, including
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(specializing in Strategic Management: https://strategy.univie.ac.at/phd/ ) envisaged starting date: 15 June 2026 (for a total duration of 4 years; Initially limited to 1.5 years, the employment relationship is
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an increased interest in adapting and developing the latest machine learning methods for the purpose of malware detection, and preliminary results are encouraging. The specific goals of this project include
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, Python, Bash). Good level on machine learning. Good level of written and oral English. Ease in a multidisciplinary environment, taste for teamwork, interpersonal skills. Scientific curiosity
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 6 days ago
skills Specific Requirements The candidate must hold a PhD in machine learning and have strong mathematical skills. Knowledge of bandit models is a plus. LanguagesFRENCHLevelBasic LanguagesENGLISHLevelGood
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for the university and funding agencies. Job Requirements: PhD qualification degree in Computer, Electrical or Electronic Engineering or related field At least 3 years of relevant research experience in AI security
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Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other
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scientists, biomedical informaticians, clinicians, and public health researchers to develop deployable, trustworthy methods that improve patient outcomes and health system operations. Key responsibilities