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ecosystems, forested wetlands, or peatlands. ● Demonstrated proficiency with statistical computing (e.g., R, Python) and spatial analysis software (e.g., ArcGIS, QGIS). ● Experience with carbon stock
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Computational Postdoctoral Researcher - Bacterial Genomics, Transcriptomics, and Single-Cell Genomic
. • Strong computational and programming skills (Python, R, Linux, and high-performance computing environments). • Demonstrated experience in genomics data analysis, evidenced by peer-reviewed publications
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-on experience in the design, construction, commissioning, and operation of complex experimental setups Programming experience in scientific computing environments (e.g., Python, MATLAB) Independent, proactive
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-structured interviews (e.g., SCID). Knowledge/proficiency with statistical software (e.g., SPSS, SAS, STATA, MatLab, Python), and database management (e.g., developing databases in REDCap, Microsoft Excel
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: Statistical programming and data analysis using R, Python, or Matlab, Spatial data analysis or GIS Whole-genome sequencing, phylogenetics, or phylodynamics Data management and reproducible analytical workflows
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reports, or research manuscripts. Preferred Qualifications ● Strong coding/programming skill (e.g., Python, C++, etc) is a plus. ● Experience with USRP prototypes is a plus. ● Experience with Nvidia
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an advantage skills in electronics, e.g., RF electronics, MRI coil design, gradient coil design, etc. programming skills with MATLAB, C/C++ or Python skills and experience in manufacturing methods, such as 3-D
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interest in contributing to both the conceptual and empirical dimensions of research Proficient in, or willing to learn, programming languages (e.g. MATLAB, Python, R) Experience with one or more of the
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related field; Strong publication record in relevant venues; Solid programming skills in Python and a modern deep-learning framework Excellent communication skills in spoken and written English; Self
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inference methods (e.g., fixed effects, IV, DiD) Advanced regression techniques - Strong programming and analytical skills (R, Stata, Python, Mplus, or similar). - Evidence of research productivity or strong