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Field
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identifying, documenting, mapping, and sharing best practices, innovations, and successful transition strategies, they contribute to generating actionable knowledge and developing a networking platform for
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communication skills. Experience in coding with Python, MATLAB, Julia, C/C++, or a similar program language. Experience with biological data analysis. Knowledge of network science and/or complexity sciences
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disruptions data and network analysis, the candidate should have a strong background in network modelling and coding. The selected candidate will also have excellent leadership ability/potential and strong
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. Experience in coding with Python, MATLAB, Julia, C/C++, or a similar program language. Experience with biological data analysis or simulations of dynamics. Knowledge of network science and/or complexity
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practices in code development and maintenance (e.g. Github/Gitlab, GitHub Actions, etc). Experience with machine learning or network-based approaches is desirable. Familiarity with FAIR data principles and
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this international network, tasked with establishing and building capability to support the Australian and international SKA science communities, thereby ushering in the next era of astronomical discovery and advanced
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Organization U.S. Department of the Interior (DOI) Reference Code DOI-USGS-2025-17 How to Apply To submit your application, scroll to the bottom of this opportunity and click APPLY. A complete
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towards this goal. The PhD research fellow will be part of the PhD programme in Computer Science: Software Engineering, Sensor Networks and Engineering Computing (https://www.hvl.no/en/research/phd
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Europe Marie Skłodowska-Curie Action - Doctoral Network FluxBEATS that integrates geological observations, cutting-edge geochemical and biogeochemical analyses, data and modeling, from modern volcanic
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the possibility of a 4th year with career-promoting work (e.g. teaching duties at the Department) The position is funded by EU and related to the Horizon Europe Marie Skłodowska-Curie Action - Doctoral Network