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: Master’s degree in Social Sciences Experience with data collection and analysis methods Strong analytical and problem-solving skills Proficiency in relevant research software (e.g., Stata, R, Python
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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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considered an asset in these positions. Applicants must also be able to demonstrate excellent ability to code with or learn computer programming languages, such as C++, C#, Python, and/or Matlab
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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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particular with Large Language Models. Solid programming expertise in Python. Be the main author in at least one journal publication in the area of AI4SE, published at a high impact journal. Experience with
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multidisciplinary team environment. Further, we will prefer candidates with some of the following qualifications: Solid background in programming using Python (PyTorch, TensorFlow), R or other languages. Experience
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multidisciplinary team environment. Further, we will prefer candidates with some of the following qualifications: Solid background in programming using Python (PyTorch, TensorFlow), R or other languages. Experience
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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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or prior experience with multilingual or low-resource NLP Programming skills in Python and proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow) and their application in high-performance
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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