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Field
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, Extensive experience in building Neural Network models and a solid foundation in mathematics. Technical proficiency in Python, C, or C++, and familiarity with Tensorflow Lite/Micro, Pytorch. Experience in
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or experience with data analysis methods (e.g. use of Stata, R, Python, or Stata) Ability to communicate complex information clearly Excellent ability to work as a team and independently including co-ordinating
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. Preferred Knowledge, Skills, and Abilities: Experience of method development in quantum chemistry. Demonstrable coding experience for example with python, fortran, C++ or others. Experience in modeling
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the master's degree has been awarded. The candidate must have good knowledge in the topic of Cryosheric Processes. Proficiency in scientific coding and data analysis programming languages, such as Python
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the master's degree has been awarded. The candidate must have good knowledge in the topic of Cryosheric Processes. Proficiency in scientific coding and data analysis programming languages, such as Python
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. Proficiency in relevant programming languages (e.g., Python, MATLAB, R) is a requirement. Familiarity with downscaling and bias correction of climate data (e.g., from CMIP/PMIP) is an advantage. Experience with
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programming skills (e.g., Python, MATLAB, R) experience with large datasets desirable proficiency in English, both written and spoken (at least C1) German is an advantage willingness to work regularly on-site
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language proficiency sufficient for reading and writing academic texts (B2+/C1) strong teamwork orientation and good communication skills Preferred qualifications: programming languages (e.g., Python
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models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques and algorithms Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly
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requirements: Solid knowledge of programming and signal processing, based on Matlab or Python. 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS: Selection criteria and corresponding valuation: the first phase