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systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization
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is developing research excellence in areas including Machine Learning, Big Data, Visual Analytics, Computational Intelligence, Machine Learning, Software Implementation and Testing, and their
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machine learning methods to scientific data (e.g. multivariate analysis, chemometrics, neural networks, classification or regression models); familiarity with large language models (LLMs) and other
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, statistical inference and machine learning, with potential applications to practical problems Independent teaching Supporting research work, participation in research projects, and assistance with teaching and
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The position will investigate knowledge-grounded and neuro-symbolic approaches to large language models and agentic AI for defensive cyber operations. The PhD project will be carried out in close collaboration
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biomedical data types Machine-learning and statistical modelling Mechanistic models of biological systems Python, R or equivalent programming environment Documented knowledge and experience in cancer biology
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frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms, distributed, intelligent, and interactive systems, networks, security, and software and database systems
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, 2026 and continues until the position is filled. Preferred start date is August 1, 2027. Contact Information Scott C. Mateer, PhD. [email protected] 912.344.3101 USG Core Values The University
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).The PhD candidate is expecting to assisting in teaching and help in laboratory on the related topic. Applicants should fulfil the following requirements: A Master's degree in computer engineering, computer
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of the central challenges on the path toward large-scale quantum computing. In this PhD project, you will investigate how machine learning can enable faster, more scalable QEC decoding. The goal is to develop new