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Python Proficiency: Demonstrate expertise in Python or a similar high-level programming language is essential for developing algorithms and backend logic Azure DevOps Experience: Familiarity with Azure
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developing a machine learning (ML) algorithm for the automated analysis of the above-mentioned mass spectra. Desirable: - knowledge in the field of Planetary Sciences - very good written and spoken English (C1
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knowledge of social media efficiency tools. Familiarity and working knowledge of social media analytic tools. Have a good understanding of the latest algorithms and methods of growth used by each platform
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Demonstrated research experience in computational physics, machine learning, or related areas. Practical experience in developing novel AI/ML models and algorithms. Experience collaborating in multidisciplinary
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of algorithms and models to realistically simulate forest ecosystem dynamics under varying conditions of land use change, forest and land management, climate variability, and other environmental stressors
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Our Machine Learning PhD Internship is a 10-week immersive experience designed for PhD candidates who are passionate about solving high-impact problems at the intersection of data, algorithms, and
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learning algorithms and methodologies that can transform society. The Student Services Lead for Professional Programs plays a critical leadership role in advancing the student experience across the School
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courses with minor algorithmic components and primarily programming courses with a focus on bioinformatics methods. Such graduate courses seek experienced bioinformatics, biotech, and data science
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arrangements. Encourage the industrial and academic partners to use UBC’s IntelCut machine tool monitoring system to transfer research algorithms to industry. The engineering activities of IntelCut will be
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portfolio in AI4Science. The Computational Sciences Department at PPPL was formed to provide a focus for computational physics and engineering. We specialize in algorithms and applied mathematics, data