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the application and integration of data, code, and computational tools in the research at the departments. Assisting with practical tasks including access to high-performance facilities, server/data management, and
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(EM) forward modeling, inversion, and applied EM studies. Within this team, the candidate will be responsible for the numerical development of inversion codes for both frequency-domain (FEM) and
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attach your motivated application including CV, diploma and if relevant list of publications. All interested candidates irrespective of age, gender, disability, race, religion or ethnic background
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or optimization. Proven experience with programming and data analysis tools. Fluency in Python, including experience writing data analysis scripts and model training code. Experience with scientific computing and
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organizations on projects across disciplines - from games to health, learning to robotics, data to code – in an environment designed for collaboration and technology transfer. The overall goal of the SDU