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environments that help learners develop deeper conceptual understanding and problem-solving skills. Topics may include multimodal representations of code, intelligent feedback mechanisms, and the cognitive
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for developing and operating their solutions. For effective collaboration, an integrated and harmonized Software Development Lifecycle (SDLC)—covering planning, documentation, coding, building, testing, and
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datasets and papers with open data and code that can serve as a basis for these exercises, then adapt these in jupyter notebooks (python or R) for student learning exercises. The Supervisor will advise
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with vibe coding, but you’re also expected to take responsibility for ensuring proper code quality control Workplace Workplace We offer A unique opportunity to work with LLMs in an Educational Technology
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and training machine and deep learning models using Keras/TensorFlow and/or PyTorch, supported by experience in statistical data analysis. You have experience with collaborative coding practices
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and refactoring source code for computational and data science applications both on the methodological and implementation side or deploying and integrating applications to adequate compute environments
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; working knowledge with research data management according to the FAIR principles and corresponding software systems (e.g., openBIS); hands-on experience with best practices for code management and
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such as Stata, R, and/or Matlab Collecting data using web scrapers and data providers like Macrobond Coding in R or Matlab on data analysis and macroeconomic forecasting Programming surveys with Qualtrics
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code, clear README, etc.). We will provide you with guidance for the implementation, but independent work, in general, is required and appreciated. The workload consists of up to 15 hours per week during
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of financial support for year 4. completed form concerning ethical issues and research requiring authorization or notification; template document provided. signed NOMIS code of conduct; template