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the following factors will be considered: a) Academic background (Master's degree average up to 16.0 points – 1 point, >16.0 points – 5 points); b) Experience in programming languages, including Python, C++, and
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familiarity with programming languages such as R or Python C4 (10%) Strong proficiency in English, capable of conducting research, writing scientific papers, and communicating effectively in an academic setting
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modeling (60%); b) Experience in participating in research projects (20%); c) Experience in programming in Python and related languages (20%). 10. Composition of the Selection Jury: Ana Isabel Pereira José
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 1 month ago
, reports, articles, projects) He she must have strong proficiency in Python and/or R for data analysis and other software for statistical and mathematical modeling He/she must have strong communication and
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Vision-Language Models (LVLMs). Knowledge and experience in pre-training and fine-tuning of LLMs/LVLMs. Knowledge of Retrieval-Augmented Generation (RAG) using LLMs. Programming experience in Python, data
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» InformaticsEducation LevelBachelor Degree or equivalent Skills/Qualifications Experience with computer programming and system administration (Python, Java Script, Web programming); Proven experience with DevOps tools
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languages for data handling, treatment and analysis (e.g. R, Python). • Experience in writing technical reports, scientific articles and other dissemination materials. • Excellent knowledge of English, both
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*• Experience in Python or another programming language (projects, GitHub repositories, courses, scientific use).• Training or experience in machine learning and data science applied to environmental or energy
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, multiparameter sondes); Basic knowledge of time series analysis and/or data management; Proficiency in programming using MATLAB or Python is required; Ability to work autonomously, with a proactive and problem
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machine learning technology. . The tasks to be carried out are: 1) Compiling a bibliography on the PINN method; 2) An analysis of libraries (in Python) for using the PINN method; 3) Research on the use