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Field
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in Python (e.g. numpy, pandas, PyTorch and/or JAX). Experience analysing complex biological, imaging or spatial datasets, or strong evidence of rapidly adapting to new data domains. Excellent
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Python programming skills. Excellent skills in written and oral English. The candidate's research proposal must be closely connected to the call and the research of MAI. Personal suitability and motivation
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, hydrologic modeling, or energy systems modeling (e.g., ParFlow, WEPPCloud, agent-based models) Proficiency in scientific programming languages (e.g., Python, R) and geospatial tools (e.g., ArcGIS, QGIS
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communication skills and the ability to work in a multidisciplinary research environment. A strong publication record or clear evidence of research productivity will be an advantage. Our lab uses Python, MATLAB
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, or laboratory automation (Python, MATLAB, or LabVIEW). PhD must have been obtained within 3 years from date of hire. Preferred Qualifications Extensive proficiency with commercial compositional reservoir
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to improving the quality and efficiency of the consortium code base. Preference will be given to candidates with a strong publication record and proven experience in Python programming, source code versioning
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, or extreme weather impacts on health. Experience with quantitative datasets and applying statistical or analytical methods using software such as R, SAS, Python, Stata, or similar tools. Familiarity with
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for gene regulatory networks, single-cell multi-omics integration, spatial omics, and variant effect mapping in complex disease. Strong method/tool dev experience required (Python/R, ML/stats
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policy, economics, statistics, or a related quantitative field Additional Qualifications Strong skills in Stata, R and/or Python and experience analyzing complex data Demonstrated experience working with
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demonstrated proficiency in programming, specifically in Python and R, as well as experience with modern deep learning frameworks like PyTorch or TensorFlow. In addition to technical skills, the candidate must