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                Field
 
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(quantitative and qualitative). They must also have experience working with large datasets and producing high-quality data visualizations and linking agronomic and genetic factors. Experience in Python/R would be
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experience in in vivo large-scale two-photon calcium imaging Programming skills, Matlab, (and/or Python) Ability to communicate complex information clearly, orally and in writing Experience in
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appointment). Strong background in statistical or machine learning methodology, optimization, or high-dimensional data analysis. Proficiency in R or Python; experience with deep learning, causal inference
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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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or Python. How to apply Candidates should apply online, carefully answer all the application form questions, and attach a curriculum vitae (with details on education, research experiences, successes and the
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models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques and algorithms Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly
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methods (e.g., field interviews, focus groups, online survey design). Proficiency with programming languages (e.g., R, Python, Matlab) for data management and analysis, computational social science, and/or
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                Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 6 days ago
. Preferencial: - Experience in programming such as Python and analysis of behavioral videos; - Good team work; Legislation and other applicable regulations: Research Fellowship Holder Statute enacted by Law no
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tissue specimens Assemble analysis pipelines using machine learning to process tissue data reproducibly and at scale Conduct analyses using programming languages such as R and Python Collaborate with other
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; or Experience with high-fidelity solvers, e.g. SU2, OpenFoam, StarCCM+, Fluent; Proficiency in programming, e.g. Python, Matlab, C; Experience utilizing high-performance computing (HPC) to parallelize workflows