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postdoctoral experience). Proficient coding skills in at least one of Matlab, R and Python. Experience and proficient in processing different types of remote sensing datasets. Experience with terrestrial
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PhD in Computer Science, Engineering or other Machine Learning-related field. • Programming experience in python, C++ or other relevant language and experience in deep neural networks • Strong
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: Proficiency in Python and major deep learning frameworks such as PyTorch or TensorFlow Familiarity with transformer architectures and large language models (e.g., BERT, GPT) Experience in building, training
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physiology Coding proficiency (e.g., Python, R) and familiarity with deep learning tools are strong assets A strong publication record, critical thinking, and collaborative mindset Application Instructions
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projects The ability to carry out and publish high-quality research Knowledge on ROS, Python, C++ and Matlab The following qualifications will be considered an advantage when applicants are ranked: Practical
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physics, and quantum error mitigation. Good programming skills in Python. Familiarity with PyTorch or tensorflow will be a bonus. Proficiency of programming skill with quantum machine learning architectures
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., Python, R, bash). At least one publication in an international peer-reviewed journal of an end-to-end software developed by the candidate Documented experience with Nextflow or Snakemake. Documented
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systems, MARL, Game Theory. Strong background in Mathematics and modelling. Good English writing and communication skills for research work. Proficiency in Python, experience with PyTorch, NumPy, and
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in scientific coding and data analysis programming languages, such as Python or MATLAB, is a requirement. Experience with running snowpack and/or Earth System Models is a requirement. Experience in
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. The candidate should have relevant scientific publications, showcasing research interest and experience in the core areas of the position The candidate must be proficient in Python, C++ or Java and familiar with