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/Python). Familirarity with AI/ML methods for scientific computing and openness to explore different approaches Very good command of English is required (spoken and written) Additional Information Benefits
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modelling Experience developing or applying models of forest dynamics Experience working with ecological and multi-scale datasets Proficiency in scientific programming (e.g., R, Python, Rust, or similar
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computationally and developing scientific software. Experience in Python is highly recommended, additional knowledge of performance-oriented modeling frameworks, either based on Python (e.g., JAX, Pytorch) or other
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Python are essential Excellent teamwork, collaboration and communication skills Proficiency in written and spoken English A stimulating, challenging and multifaceted research environment Good integration
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(preferably Python), multiple years of programming experience as well as profound knowledge of professional computer-aided design and 3D modelling In addition, you have experience in CAD/CAM (preferably McNeel
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programming languages (e.g., MATLAB, R, or Python) Excellent communication skills You will have in-building access to mouse laboratories as well as access to state-of-the-art research equipment in metabolomics
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against experimental data. Proficiency in Python, together with good software engineering practices such as version control and testing, is expected. Experience with high-rate dynamics, cavitation
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, ICML, ICLR) Proven ability to conduct independent, high-quality research Proven ability to write well-documented code in Python Strong motivation to work in a collaborative team environment and to
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-… Requirements Research FieldBiological sciencesEducation LevelPhD or equivalent Skills/Qualifications Your profile PhD degree in natural sciences Proficiency in python and/or other coding language Proficiency in
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statistical genomics, computational biology, computational genomics, or animal genomics. Experience with a programming language (e.g., python, R) and basic working knowledge with high-performance computing