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Field
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Qualifications • Master's degree in Bioinformatics, Data Science or related fields. Skills and Preferred Factors Proficiency in programming languages applied to data science (e.g., R, Python, and Bash, among
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. Good programming skills (Python and C/C++ preferred). Proficiency in English and excellent communication skills and teamwork. Work Plan: The selected candidate will join the Intelligent Systems Group and
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to engineering phenomena, especially in the areas of structural engineering; Have applied knowledge in the finite element method; Have proven experience in software development in C, C++, C# or Python programming
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pipelines for data analysis, programming in C++ and Python, Intelligence Artificial. Proficiency in English (written and oral communication) will also be valued. 3. Work Plan: This work plan includes
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applied to data science (e.g., R, Python, Bash, and SQL, among others) for processing, statistical analysis, and workflow automation. Practical experience in the processing, analysis, and visualization
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Experience & Adaptive Connectivity for Cooperative Mobility". Scientific Area: Networks and Services Group: Networked Systems – Po Work Objectives: - Development of a Python application for anomaly detection
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Faculdade de Ciências Médicas|NOVA Medical School da Universidade NOVA de Lisboa. | Portugal | 1 day ago
the area of programming in python, or microscopy analysis or related fields. Work plan The selected fellow will join the project as a researcher and perform the following tasks under the scientific guidance
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of the candidatures. Further information at https://www.dges.gov.pt/en/pagina/degree-and-diploma-recognition Where to apply Website https://www.it.pt/ Requirements Research FieldEngineering » Electronic
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at https://www.dges.gov.pt/en/pagina/degree-and-diploma-recognition Where to apply Website https://www.it.pt/ Requirements Research FieldEngineering » Electronic engineeringEducation LevelMaster Degree
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scientific programming, preferably in Python, for processing, analyzing, and visualizing experimental data; 6) Experience in curating, harmonizing, and managing experimental databases; 7) Experience in