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of knowledge-driven models, leveraging Bayesian statistics and causal inference for calibrated uncertainty, distribution-shift detection, and safety guarantees. You will be will working within the Center
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of knowledge-driven models, leveraging Bayesian statistics and causal inference for calibrated uncertainty, distribution-shift detection, and safety guarantees. You will be will working within the Center
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. The primary objective of SURE-AI is to create a new generation of algorithms for inference and decision-making by pushing the boundaries of computational techniques. The research emphasizes efficiency in
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coursework in probability and statistical inference, a statistics-focused Master’s thesis, or relevant publications. Foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in
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competence in statistical theory and methods. Such competence can be documented by graduate-level coursework in probability and statistical inference, a statistics-focused Master’s thesis, or relevant
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publication(s) The following qualifications will count in the assessment of the applicants: Familiarity with Bayesian estimation techniques Familiarity with machine learning methods Proficiency in IRT Personal
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: Familiarity with Bayesian estimation techniques Familiarity with machine learning methods Proficiency in IRT Personal skills A collaborative, friendly, and team-oriented style of work Ability to join
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of past warm periods in diverse geophysical datasets including, high resolution 3D and 2D seismic, sub-bottom profiler, regional 2D seismic and petrophysical logs; infer complex Earth system process
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background in archaeology or a cognate discipline, with demonstrated experience of work with large datasets, databases and spatial analysis and tools A track record of high-quality journal publication
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in freely moving rats while tracking behavior in detail in a novel, closed-loop pursuit task. They should have a good intuition for rodent behavior, steady hands, strong self-motivation and a