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campaigns on HPC resources using Python-based scientific workflows. Publish results in peer-reviewed journals, present findings at international conferences and contribute to the supervision of Master’s
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CCSE - Associate Professor in Computer Science - Integrated Preparatory Cycle & Engineering Programs
science across the preparatory cycle and the engineering and Bachelor programs: computer-science foundations for engineers, algorithmics and data structures, programming in Python, numerical methods, and
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. Processing and analysis of satellite observations related to air quality and greenhouse gases. Scientific programming in Python, R, Fortran, MATLAB, or similar languages. Duties and Responsibilities
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-economic issues. Proficiency in urban modeling tools such as MATLAB, Python (especially libraries like Pandas, NumPy, SciPy, GeoPandas, etc.), and R. Advanced skills in predictive modeling and machine
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. Proficiency in PV systems, instrumentation, and performance measurement. Experience in processing environmental data (Python, R, MATLAB). Interest in integrated approaches (energy–environment
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Engineering. Solid knowledge of AI/ML, embedded systems, and IoT architecture. Programming skills in Python, ROS, TensorFlow, or MATLAB. Strong interest in applied AI and autonomous systems
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their chosen research area. Criteria of the candidate: PhD degree in Computer Science or Applied Mathematics Strong publication track record in relevant research areas Proficiency in Python
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, Agricultural Data Science, or related field. Strong track record in remote-sensing imagery and/or time-series analysis and ML/DL for spatio-temporal data. Advanced Python skills and experience with ML
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learning applied to chemical reaction prediction or retrosynthesis (e.g., reaction templates, template-free approaches). Proficiency in Python programming and familiarity with ML frameworks such as
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Science, Environmental Science, Remote Sensing, or related field Experience in atmospheric modeling, satellite remote sensing, or machine learning Programming skills (Python or R) Strong publication