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Quantification Python and ML frameworks (TensorFlow, PyTorch, JAX) Reproducible and open-science practices Experience with geospatial, environmental, or climate data is advantageous but not required. What We Offer
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skills with the ability to connect theoretical modeling to practical, experimental data. experience with relevant computational tools (e.g., MATLAB, Python, or similar scientific programming environments
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Neural Networks Deep Learning and Uncertainty Quantification Python and ML frameworks (TensorFlow, PyTorch, JAX) Reproducible and open-science practices Experience with geospatial, environmental
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sample preparation Desirable Qualifications Prior experience with negative ion mode MS is an advantage Interest in computational proteomics workflows Programming or scripting skills (e.g., Python, R
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Programming experience (e.g., Fortran, Python, shell scripting) and HPC workflows Experience working with operational forecasting systems and advisory tasks We are looking for a researcher with a strong
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types. Familiarity with data preprocessing pipelines for high-throughput omics data (e.g., Nextflow). Strong programming skills in Python (Data and Machine Learning stacks). Experience with version
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datasets. Proficient in Python and the various numerical packages (e.g. NumPy, Pandas, etc) Ability to work both independently and as a part of a team. Excellent communication and writing skills in English
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programming skills in Python and/or R Familiarity with machine learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn) Excellent problem-solving, organizational, and communication skills Demonstrated
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experience in several key languages, e.g., Rust, C++, or Python (not MATLAB), algorithms, and machine learning is necessary as well as excellent communication skills in English. Applicants with experience in
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., Python, Bash) Experience with Git, CI/CD workflows, and collaborative development practices Strong communication skills and ability to work both independently and collaboratively Interest in educational