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modelling, preferably WRF Experience of scientific programming and running code on HPC systems Experience with Fortran, Python and Linux Shell Any of the following is advantageous but not essential
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. Develop data processing pipelines covering drift correction, sensor I/O, and visualization implemented in Python. Active dissemination of the results in scientific articles and participation in national and
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developed python-based EM forward operator. Contributing to the development of a freeware software package that offers both forward and inverse modeling capabilities for FEM and TEM data. Collection of FEM
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related field Experience with Earth System or biogeochemical modelling Strong programming skills (e.g., Python, R, MATLAB) and experience with advanced machine learning modelling A strong interest in
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, electrical engineering, communication engineering, computer science, or a related field. Documented experience with deep learning techniques (e.g., CNNs, Transformers) Strong programming skills in Python and
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of the following qualifications: Extensive experience in programming using Python, R, or other languages Research experience in greenhouse gases, or ecological experiments Insight into global
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possible. It is strictly required that you have experience with: Scientific programming, preferably in python and/or MATLAB and/or C++ Derivation and implementation of finite element methods (FEM) in code
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, Python and QGIS Good knowledge of geology and hydrogeology in aquitard-aquifer systems Experience in collaborations with partners from consultancy and public authorities Ability to work both in a team and
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environment research experience working with real-world non-linear dynamic data, networks, and ideally with applying coupled oscillator models strong programming skills in e.g., Python previous research
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protein design programs and analysis tools is crucial. Knowledge of programs like Rosetta, RF-diffusion, FoldX and python is necessary. Apart from very good modeling skills, knowledge in protein production