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quantitative microscopy (live-cell imaging, high-content screening, or single-cell/single-bacterium imaging) Comfort with image analysis pipelines and scripting (Python), experience integrating ML-based image
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proficient in Python; prior experience with the FEniCS library is a plus; C++ knowledge is an additional asset You have strong computational skills, including the implementation of simulation and optimization
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computing environments, such as Python, R, or MATLAB; A strong publication record appropriate to the candidate’s career stage; The ability to work both independently and collaboratively in
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proficiency in one or more programming or scientific computing environments, such as Python, R, or MATLAB; A strong publication record appropriate to the candidate’s career stage; The ability to work both
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integration and trajectory inference Proficiency in Python and/or R Interest in developmental and human biology is highly valued, but not required Strong collaborative mindset and ability to work across
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Python and experience with GPU processing of large-scale datasets. Excellent written and oral communication skills in English. We also value applications from people with the following experience
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scientific programming in Python and experience with GPU processing of large-scale datasets. Experience with inverse problems and 3D reconstruction methods for tomography, laminography, or a closely related
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Python and experience with GPU processing of large-scale datasets. Excellent written and oral communication skills in English. We also value applications from people with the following experience
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skills Proficiency in at least one programming language for geospatial analysis: Python (rasterio, geopandas, scikit-learn), R or Google Earth Engine. Experience with open-source tools (QGIS, GRASS GIS
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interest in contributing to both the conceptual and empirical dimensions of research Proficient in, or willing to learn, programming languages (e.g. MATLAB, Python, R) Experience with one or more of the