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Computer Science, Artificial Intelligence, or related field. Proven experience in machine learning and neural network architectures. Strong programming skills in Python and familiarity with PyTorch. Experience with
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fields. Proficiency in Python (5+ years) and some experience with C++ or Rust. Experience with modern software development tools (e.g., version control, CI/CD, testing, documentation). Excellent
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to work with people from different disciplines and backgrounds Programming experience using languages such as Julia, Python, R, etc. At least one of the following: Experience in applying machine learning
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microbiology/bioinformatics or nutrition (essential), experience with metagenomics (desirable), bioinformatics (experience using R or Python), multi-omics, and biochemistry. Communication capability in English
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(e.g., using Python, or similar tools) is advantageous. Good communication skills in English (written and spoken). Ability to work collaboratively and supportively in an international research
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., segmentation, denoising, feature extraction), including both classical techniques and AI-based approaches Proficiency in Python and experience with tools like napari, scikit-image, OpenCV, and Pytorch
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Technical Proficiency: Familiarity with engineering tools with focus on design automation Experience in programming (e.g. Python) or machine learning and a desire to deepen your expertise Experience in
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ecophysiology. You must have good statistical skills, experience with fieldwork, and programming experience (e.g., in R or Python). A good standard of written and spoken English as well as a driver’s license are
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, computational genomics, or animal genomics. Experience with a programming language (e.g., python, R) and basic working knowledge with high-performance computing clusters is required. A MSc degree in genetics
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areas above) and their grades. Strong programming skills (i.e., Python and main Machine Learning frameworks such as Pytorch). Experience with scientific writing (e.g., reports, theses, and scientific