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/training. Preferred Qualifications: Demonstrated skills (or ability to learn quickly) in any of the following: programming (especially Python), data science, machine learning, and statistics. Previous
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information about our institute here: https://www.fz-juelich.de/en/ias/ias-8 Your Job: Develop physics-aware simulations of growing cell populations, including their spatiotemporal manipulation in microfluidic
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includes geologists, atmospheric scientists, paleontologists, and oceanographers. Additional information about the department may be found at: https://science.gmu.edu/academics/departments-units/atmospheric
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Systems, Quantum AI, Blockchain AI, AI for Autonomous Systems Foundational courses (for Connect pathway students): Python programming, Mathematical Concepts, Research Methods and Scientific Writing
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in machine learning and/or advanced analytical methods, experience working with complex or large-scale datasets, and strong programming skills (e.g., Python or R). You will be able to communicate
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software (e.g. ArcGIS, QGIS) and coding environments (e.g. Python or R), collaborating across LUMHR themes, and supporting interdisciplinary research activity. Teaching support may be required, up to a
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Familiarity with use of Reference Managers Desirable Skills: Quantitative/Data Visualisation skills (Python?) Experience in data management Postgraduate or relevant research experience Works well within a team
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Materials, Bioinspired Materials and Sustainable Materials. For more details, please view https://www.ntu.edu.sg/mse/research. We are seeking a highly motivated Research Fellow to join our dynamic team
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Learning for Cybersecurity, AI for 3D Imaging, Recommender Systems, Quantum AI, Blockchain AI, AI for Autonomous Systems Foundational courses (for Connect pathway students): Python programming, Mathematical
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), Excel (VBA and macro automation), SQL, and Python. Assist with data analysis and preparation of results (tables and charts) for presentations, publication, or reports including internet distribution using