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/PhD) or related field. - Simulation & data: TRNSYS (or similar), time-series processing; Python (pandas/numpy). - Experience with GIS and/or climate/solar datasets (e.g., METEONORM, PVGIS
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Geográfica (SIG). - Dominio en modelización estadística de datos y de software estadístico y SIG (R, QGIS/ArcGIS, Python). - Experiencia en la redacción de textos científicos y buen nivel de comunicación
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imprescindible, se valorará positivamente en el proceso de selección la titulación de Máster y la experiencia/conocimiento en algunas de las siguientes áreas: lenguajes de programación (Python, JavaScript
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and scored: A. Knowledge of Matlab, Python, R and/or C++ (advanced level). These will be assessed based on accredited training hours (0.5 points for every 10 hours of training, up to 5 points for each
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Matlab, Python, R and/or C++ (advanced level). These will be assessed based on accredited training hours (0.5 points for every 10 hours of training, up to 5 points for each course) and accredited project
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positivamentela experiencia/conocimiento en algunas de las siguientes áreas: lenguajes de programación (Python, JavaScript), técnicas y herramientas software de análisis de datos, machine/deep learning (Pandas
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, oriented in Energy Systems. Minimum 3 years of experience in energy system modelling and/or control. Knowledge of Energy Markets, Excellent knowledge of Python Spoken and writing capabilities in Spanish
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. Proven experience (>4 years) in energy systems storage modelling or energy optimization. Experience in scientific writing (papers, conference proceedings). Proficiency in Python or similar programming
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biology and laboratory techniques (e.g., qPCR, immunofluorescence, among others). Knowledge of image analysis using ImageJ or similar software. Proficiency in MATLAB and Python will be considered
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Knowledge of Matlab, Python and software for signal interpretation Experience in laboratory for biomedical signal acquisition Experience in joint projects with Hospitals or Health institutes Scientific