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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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. • Excellent Python programming skills and strong hands-on experience implementing, training, and evaluating deep-learning models and research codebases. A strong track record in machine learning or closely
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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