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Field
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with large-scale data construction and empirical research • Programming skills (R, Stata, or Python) Applications should be sent by e-mail, together with significant documents, indicating the reference
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interpret research datasets, drawing meaningful conclusions using appropriate statistical methods and scientific reasoning. Develop and optimize computational pipelines, scripts, and workflows using Python
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 5 hours ago
geospatial data processing and python programming. Candidates should also have knowledge of optical, lidar, and ground penetrating radar sensing systems and understanding of pavement structures and condition
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 14 hours ago
require terminal degree and licensure. Required Qualifications, Competencies, and Experience Proficiency with statistical or data analysis software (e.g., R, Python, SPSS, MATLAB). Ability to manage and
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research and developing decision support systems. The candidate would also assist in writing python/R programming scripts to optimize processing time, making the current decision support systems more
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lead to a PhD position at SPMS in NTU Singapore (based on performance). Key Responsibilities: Contribute to the development of algorithms Develop codebase in Python and perform large-scale simulations
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also include trouble shooting capabilities. Desirable skills include working knowledge of Linux, FORTRAN, Python and C++; experience with machine learning, parallel computing and high-performance
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one of the following programming languages: C++, PERL, Python, R, Java Experiences with high-throughput sequencing data (WGS, WES, RNA-Seq, ChIP-Seq) analysis Excellent oral and written communication
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mechanics and analysis Experience with the following: Structural health monitoring (SHM) Finite element modeling (e.g., ABAQUS, SAP2000, ANSYS) Machine learning / AI (Python, TensorFlow, PyTorch) Demonstrated
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programming skills in Python Experience with scientific Python tools such as pandas, scikit-learn, matplotlib, and Jupyter; experience with PyTorch is a plus Familiarity with microbiome data analysis