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Paid Internship
Work Mode
Time Spent
Required Degree
Duration

24Open Positions

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Student Employee

Technische Universität Wien
Found 2 weeks ago
Location
Wien, Austria
Time
Part-time
Work Mode
Not disclosed
Salary
EUR 1,379.60/month gross, 14 times/year for 20 hours/week
Visa Help
Not disclosed
Last Verified
2 weeks ago

Education

  • Bachelor
  • Master

Skills & Qualifications

Technical Skills

  • APIs
  • data pipelines
  • data integration workflow
  • CI/CD pipelines
  • DevOps practices
  • data orchestration tools
  • kowledge graphs
  • graph databases
  • Large Language Model

Soft Skills

  • Team- and communication skills
  • precise work
  • Strong analytical and debugging skills

Job Description

The successful candidate will contribute to this process in a supporting capacity by carrying out the following tasks: * Support the engineering and integration of advanced AI software components * Contribute to the design and development of various data wrangling phases (e.g., cleaning, integration) to help harmonize different data sources * Assist in interlinking TU Wien’s data sources with online platforms to identify research trends and enable comparative analyses * Support navigation and information extraction from knowledge graphs * Support the construction of scientific prototypes and proofs-of-concept to help demonstrate successful approaches * Provide regular input to consultations and assist in the preparation and presentation of results to stakeholders

Requirements

  • Enrolled in a relevant study program in the field of Informatics, Business Informatics or Data Science; No completed Master- or Diplom Study in these fields
  • Very good programming knowledge
  • Familiarity with APIs, data pipelines and data integration workflow and with CI/CD pipelines and DevOps practices
  • Understanding of data orchestration tools and kowledge graphs and graph databases
  • Strong analytical and debugging skills
  • Team- and communication skills and precise work

Related Field

  • AI & Machine Learning

Related Subfield

  • Applied Machine Learning

Nice to Haves

  • Experience with cloud or university computing infrastructure and in similar data science projects
  • Familiarity with data governance and reproducible research workflows
▶Apply Now

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