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pipelines (e.g., handling transcriptomic or scRNA-seq datasets using R or Python). Special Instructions to Applicants: In order to be considered, you must upload your cover letter and resume. What We Offer
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experimental workflows Specific Requirements Experience in Python or similar tools for data analysis, visualization, and automation would be an advantage, especially for handling large experimental datasets and
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with scientific programming and quantitative data analysis, particularly in Python, is welcomed. Experience with droplet generation, thermal diagnostics, image processing, or automated experimental
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of statistical and quantitative methods for analyzing complex, highdimensional datasets Good understanding of biochemical principles, including mass spectrometry Good programming skills (Python and/or R) Strong
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datasets High proficiency in data analysis and statistical programming using R and/or Python. Experience working in high-performance computing (HPC) environments for large-scale analyses and with workflow
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magnetic resonance imaging (MRI), such as arterial spin labeling and diffusion tractography using programming scripts, such as Python and C++ Self-driven, motivated, and creative in designing image analysis
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experience using statistical software such as R, Stata or Python, together with the ability to manage and analyse complex datasets and contribute to scientific publications and presentations. You will also
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software that allow time-evolving models of complex systems to be calibrated against sparse, indirect, and uncertain observations. The group develops and maintains an open-source Python framework
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of research proposals and advise graduate students. Demonstrated leadership/managerial and organizational skills. Full professional proficiency in one of the following languages: Python (including PyTorch and
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in computational fluid dynamics Experience in computer programming, in particular Python and Matlab, and in CAD and CAE tools Ability to work independently and also to enjoy collaborating with others