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. Demonstrated high level of achievement in related research productivity and academic writing. Technical skills in computer programming, algorithm development and deep learning model implementation, and practical
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(25260475) Responsibilities: The Department is recruiting a scholar at the rank of Research Assistant Professor in computational mathematics, machine learning, scientific computing, statistics, and related
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self-adaptation capabilities. Three major challenges have been identified: (P1) modelling uncertain environments where robust, weakly supervised machine learning algorithms can be deployed to irrigate
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the Research Promotion Foundation, RIF, (EXCELLENCE/0524/0337), Title: “Machine Learning for Intelligent Insect Monitoring” and proposes an automated early warning system that will be able to detect and classify
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will be integrated with statistical and machine-learning methods to classify polarity states and identify quantitative signatures predictive of metastatic behavior. The project will deliver transferable
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deadline Experience with urban acoustic monitoring or transportation noise assessment Programming skills in Python Knowledge of machine learning techniques applied to acoustic or environmental data
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for large-scale data analysis, complex simulations, and the development of next-generation artificial intelligence and machine learning models. The responsibilities will include: • Developing and teaching
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. Integrate physical laws, experimental data, and simulation results into unified machine learning frameworks to improve model robustness and generalizability. Conduct data preprocessing, model training, and
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-effectively predicting the rate of massively multicomponent organic, or organic-enhanced, new-particle formation in the atmosphere. We will combine our molecular-level model development with machine learning
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to significantly extend our existing team’s capabilities for data scoring and analysis (e.g., with expertise in natural language processing, machine learning, or computational modeling). Finally, the