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This research focuses on developing and evaluating methodologies for the optimal design of control charts within the framework of Statistical Process Control (SPC). The study aims to determine the
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Assistant Lecturer/ Lecturer (Continuing Defined Periods Academic Employment) - Department of Econometrics and Business Statistics Job No.: 687217 Location: Various campus locations Employment Type
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with the supervisors. Required knowledge The successful candidate must have expertise in one or both of ML/statistics and XAI, and at least be conversant with the other area.
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Minimum Message Length (MML) is an elegant information-theoretic framework for statistical inference and model selection developed by Chris Wallace and colleagues. The fundamental insight of MML is
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of statistical signal processing, inference, machine learning and dynamical systems theory to develop new semi-analtyical filtering approaches for state and parameter estimation to infer neurophysiological
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Statistical Methods, Automated Planning and/or Reinforcement Learning.
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. Required knowledge Strong background in machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch
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-Response Discovery Establishing frameworks and parameters around Value-Based Digital Health Implementation Challenges in AI for Pathology Optimal Design of Control Charts for Enhanced Statistical Process
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testing approaches that can be used to verify that machine learning models are not biased. Required knowledge Software engineering, software testing, statistics, machine learning
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quantitative disciplines such as data science, mathematical statistics, actuarial science or public health or psychology with strong statistical training. You can check your eligibility with the PhD readiness