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Field
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, urban stormwater, and/or water reuse technologies · Experience with computer programming (e.g., MATLAB, Python, or R) · Experience with statistical and process-based modeling of water resources systems
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utilizing modern programming tools and languages tailored to the project's requirements (e.g., Python, JavaScript, Django, among others). The activities may also include testing and validation on both
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and data analysis tools commonly used in bioinformatics (e.g., shell scripting, Python, R). Solid understanding of omics data, including metagenomics, RNA-seq, and metabolomics. Experience with
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Qualifications: A PhD in Physics, Astrophysics, Data Science or a closely related discipline is required. Strong proficiency with programming, especially in python and optionally in C/C++. Strict adherence to open
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experience with empirical research methods. Candidates with research experience are strongly preferred, especially those with programming experience in Stata, SAS, R, and/or Python. Candidates need not be
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to scientific problems, preferably with materials or polymer datasets. Proficiency in Python and scientific computing libraries; familiarity with machine-learning frameworks and data processing tools. Experience
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to NeuroPathways Familiarity with quasi-experimental methods for causal inference Familiarity with administrative register data or other types of big data Familiarity with R, Stata, Python, or other relevant
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the OpenQuake platform. The development will be carried out in a collaborative environment, using modern programming tools and languages aligned with the project's needs (e.g., Python and QGIS). 8 - Location
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(e.g., carbon, nutrients, oxygen) or transient tracers such as CFC-12 and SF6, is required. Proficiency in MATLAB or Python is required. Applicants must be able to take part in a nearly two-month-long
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., Seurat, Scanpy, DESeq2). Experience with spatial transcriptomics and multi-modal data integration is highly desirable. Proficient in Python, R, and ML libraries such as PyTorch or TensorFlow. Strong