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Field
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quantitative methodological skills in handling detailed spatial data, including various econometric techniques and machine learning approaches; a thorough understanding of empirical, explanatory research; a
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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
PhD candidate to develop and apply ultra-fast machine-learning interatomic potentials (UFPs, Xie et al., npj Comput. Mater., 2023, 10.1038/s41524-023-01092-7 ) for long, multi-million-atom molecular
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on Graphs: Symmetry Meets Structure (LOGSMS). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing
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disconnectivity in brain networks relates to symptom networks and recovery trajectories in psychiatric patients. Apply and further develop methods from network science, machine learning, and computational
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the European Research Council - ERC COG 101088763. The work for this position is in the area of Machine Learning and Natural Language Processing. We are offering We offer a challenging position with the
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of the state of the art in machine learning for generation of artificial data; - identify and select the appropriate methods for the study in question; - develop the research capacity through the application
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structures, access to space, multidisciplinary design and concurrent engineering, uncertainty treatment and optimisation, machine learning. (https://www.strath.ac.uk/ ) Task description for your Individual
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for mitigation of marine-induced hazards, application of machine learning techniques and opportunities provided by AI. Even though the listed advanced topics are mostly at the cutting edge of fundamental research
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 19 days ago
skills. Have very good knowledge of machine-learning and data science methods, especially for timeseries data Have very good programming skills in programming languages such as Python. Have previous
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Python for scientific computing – experience with data analysis and basic signal processing – foundations in machine learning and interest in developing advanced AI models – familiarity with Linux