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Field
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dashboards • Design and implementation of a web dashboard for visualizing energy consumption on an urban scale. • Use of tools such as Python (Dash, Flask), JavaScript, Plotly, Mapbox, Leaflet, or equivalent
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with Linux, Docker, MongoDB, PostgreSQL, and Opal technologies; - Experience with CI/CD methodologies and technologies; - Software development experience based on JavaScript (ReactJS, NodeJS) and Python
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the required test scripts in Python/Matlab. c) Propose a test plan and a test setup using semi-automated test procedures. Task 3: Test procedure validation (6 weeks) a) Conduct the proposed test plan
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Biology or overall large-scale sequencing data analyses; b. Proficient in R and Python scripting; c. Experience in analysis of transcriptomic data (RNAseq) enclosing large sample size; d. Experience in
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/or evolutionary spectral synthesis codes; c) proficient use of the astronomical data analysis software package ESO-MIDAS; d) surface photometry; e) programming in Python and at least one high-level
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on the applicants' enrolment in study cycle or non-award courses of Higher Education Institutions. Preference factors: - Experience with different programming languages, including C, Python, Go, and Rust
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or related field;* Solid knowledge in machine vision and deep learning (e.g., TensorFlow, PyTorch, OpenCV); Experience in Python programming (focus on libraries for data analysis and AI); Previous
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, resulting in exclusion from this call. Specific Requirements Preferential factors: Proficiency in programming in the Python language, as well as familiarity with LLMs and VLMs. LanguagesENGLISHLevelExcellent
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with instrumentation; Experience in applied optics; Proficiency in Python. Funding Entity: project LIBScan, with reference 17490 (COMPETE2030-FEDER-01205900) Co-funded by ERDF - European Regional
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impacts on health. Preference is given to candidates with knowledge of Python programming. Work Plan Development of methodologies for the analysis of the contribution of waste processing systems and sludge