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Field
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) Proficiency in programming and data analysis tools (Python, R, MATLAB, SQL or similar) Ability to work independently and within an international multidisciplinary team High level of English Specific
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. R, Python, MATLAB or similar) Ability to integrate molecular, clinical and experimental data in translational research projects Experience in scientific communication, including publications and
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Research Engineer - Tools developer for LSQUANT platform (Theoretical and Computational Nanoscience)
Python or Java script familiarity with the following tools will be highly appreciated: Monfgo DB , React an dreact workflow, Google API´s, Pytorch Professional Experience: Programing in PYTHON/C languages
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) Participation in R&D projects (EU, national, or regional) Scientific publications (JCR journals, international conferences) Advanced programming skills (Python, Java) and technical portfolio Academic Training (30
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or equivalent Skills/Qualifications Conocimientos de programación (Python). Empleo de herramientas de modelización numérica geotécnica (FLAC, PFC). Specific Requirements Conocimientos en Ingeniería Civil
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modeling with SUMO. Programming transport modes with Python. Integration of climate constraints into a transport model. Emergency and disruption management. Where to apply Website https://sede.uvigo.gal
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robots for facade operations. Programming in MatLAB and Python. Navigation in GNSS-denied environments. Publicacion of scientific papers. Development of project deliverables. Where to apply Website https
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to interdisciplinary discussions Office, GIS (Arc/Q), R, Python (basics) English, Spanish (Italian, German, Dutch, Polish beneficial) Strong experience with spatial assessments. Early leadership experiences at junior
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Experience working as a developer in Linux environments Good programming skills in Angular and React libraries Basic programming in Python Knowledge of Flask and Docker A bachelor's degree in informatics or a
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) or equivalent. C. Demonstrable experience* in the field of tasks to be performed in the project (max. 3.5 points): - Knowledge of Deep Learning (max. 0.75 points) - Python programming language and environments