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hydrological modeling at catchment scale, and familiarity with modeling tools. Proficient in statistical analysis and programming languages such as Python, R, or MATLAB. Strong written and verbal communication
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the use of bioinformatics tools for metagenomic and transcriptomic data analysis (e.g., QIIME, DADA2, R, Python). Demonstrated ability to independently design and conduct experiments, analyze data, and
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Industrial Engineering, Operations Research, Mining Engineering, or a related discipline. Strong track record of publications in simulation, optimization, or industrial engineering. Proficiency in Python and
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quality (PM2.5, CO2, Nox, etc.) and energy monitoring (voltages, currents, battery charge/discharge cycles); Proficiency in languages commonly used in IoT, such as C/C++, Python, and JavaScript. Expertise
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satellite imagery (e.g., Landsat, Sentinel) and other remote sensing data sources. Proficiency in programming languages such as Python, R, or MATLAB for data analysis and algorithm development. Knowledge
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programming languages such as Python, R, or MATLAB for data analysis and algorithm development. Knowledge of machine learning techniques and statistical modeling for environmental applications. Excellent
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and avoid indirect land use emissions from the clearing of new forests. Requirements Programming skills, preferably in Fortran, Python / R Knowledge of remote sensing data processing and analysis
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charge/discharge cycles); Proficiency in languages commonly used in IoT, such as C/C++, Python, and JavaScript. Expertise in firmware development and optimization for microcontrollers and embedded systems
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learning; Proficiency in programming languages such as Python and R. Strong experience working with climate and remote sensing datasets for environmental applications. Experience with high-performance