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and quantitative science. Fluency in English, both verbally and written, and good communication skills are a must, as is experience with a higher programming language (e.g., Fortran, C, R, Python). You
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such data; hands-on experience in scaling up and/or parallelizing codes on HPC systems using languages such as e.g., C/C++, Fortran, Python; solid knowledge of parallel programming models (e.g., MPI, OpenMP
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automating the detection of individual tree species in forests using deep learning. Specifically, you will: Focus on the application of deep learning techniques in Python to process spatial and aerial data
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experience with computer modelling, (e.g. agent-based modelling), as well as good grasp of machine learning, forecasting techniques, scenario planning, optimisation, Python and GIS. Good knowledge of English
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knowledge of R/Bioconductor and/or Python Working experience with GNU/Linux operating system Enthusiastic about statistical and bioinformatics data analysis Strong communication skills and a team-oriented
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information and validating component lists. Matching BOMs with manufacturer and trade data from the Pharmaceutical Supply Atlas. Writing Python scripts for data extraction and preprocessing. Collaborating
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, and tree physiology. Willingness to travel and undertake extended fieldwork for data collection. Driving license. Experience in ecological data analysis and statistical programming (R or Python
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, or Python Basic knowledge of databases (i.e., SQL) and JavaScript language is a plus Workplace Workplace We offer Starting in July or August and continuing until December 2025 with possibility to extend
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. Job description Your task would be to help us in setting up the data pipeline for a synthetic population and travel demand model using Python (i.e., pandas, NumPy, geopandas, MatplotLib, etc.). You will
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Programming experience (Python, MATLAB, or similar) Required people skills: Highly self-organized, structured, and motivated to explore new techniques Strong problem-solving mindset and willingness to tackle