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project 1. Only 2% of the human genome sequence codes for proteins, while most of it consists of noncoding sequences, including regulatory factor binding regions, transposable elements, pseudogenes
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of reproducible code through code sharing platforms, version control, workflow languages and container solutions. Documented ability of responsible and legally compliant adoption of machine learning/AI methods
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” are central concepts to us, and we value experience in the development of reproducible code through code sharing platforms, version control, workflow languages and container solutions. Documented ability
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of reproducible code by using code sharing platforms, version control, workflow languages and container solutions is a merit. Experience in training deep learning-based models on HPC-resources is also meriting. A
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good software engineering habits — modular, well-documented, reproducible code. Are comfortable working in interdisciplinary teams and can communicate effectively across computational and experimental
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engineering practice, collaborative development experience (e.g. Git/GitHub), and ability to use AI-assisted coding tools effectively. Strong communication and collaboration skills, with the ability to work