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; Experience in Python and R programming, and shell scripting - information provided in the CV and/or in the motivation letter; Proven scientific experience in the above-mentioned topics, demonstrated by
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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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on Debian and its derivatives. c. Knowledge of the protocols of Internet communication. d. Knowledge of shell scripting, preferably in Bash or Python. e. Knowledge about programming language Ruby. f. Interest
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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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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | about 1 month ago
Python or others (Essential) Basic knowledge of the mechanical behaviour of composite materials Experience in writing technical reports, scientific papers, or project documentation Initiative, sense
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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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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | about 1 month ago
Engineering ii. Basic knowledge of Python iii. Basic CAD modeling skills acquired during academic training iv. Introductory familiarity with numerical simulation (e.g., finite element method and meshless
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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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, 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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for spectral and spatial data pre-processing, as well as on machine learning algorithms, chemical map reconstruction, and algorithmic correction of galvanometric scanning.; Training will cover Python programming