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Master's Thesis Worker - Beyond Human-in-the-Loop Learning

Technology, Data & Digital · Data, AI & Analytics · Data Science · Software Engineering

In short

This Master's thesis explores the future of data ecosystems and human-AI interaction in commercial vehicle R&D, focusing on system resilience and evolving engineering roles. The research will contribute to building resilient data systems and preparing engineering teams for increasingly autonomous and connected technologies within TRATON Group.

Responsibilities

  • Conduct a pre-study of research and organizational expectations concerning AI-enabled R&D, data ecosystems, system resilience, and future engineering work.
  • Select a relevant research context within Battery & Charging in dialogue with supervisors and stakeholders.
  • Design and conduct a mixed-method study with relevant domain experts and other stakeholders.
  • Explore how domain teams' responsibilities, decision-making, and oversight may change as data systems become more connected and automated.
  • Examine what resilience means for the selected data systems and infrastructures, including how they remain reliable and adaptable as conditions change and how people can recognize when attention or intervention is needed.
  • Investigate the capabilities and skills engineers may need to understand, assess, and work with these systems.
  • Develop an evidence-informed future scenario, framework, or early-stage indicators to support discussion of system resilience, future capabilities, and investment milestones.
  • Translate the findings into recommendations for resilient data ecosystems, B&C capability development, and AI investment planning for analytics enablement.

Requirements

  • An educational background in human–computer interaction, cognitive science, industrial engineering, autonomous systems, data science, computer science, or a related field.
  • Previous experience in mixed-methods research and creative research approaches, such as speculative design, provocative design, or practice-based inquiry.
  • Experience from research, academic, or professional projects involving digitalization, data-driven practices, AI, or other emerging technologies.
  • An interest in one or more of the following areas: digitalization, human–AI interaction, more-than-human design, datafication, or socio-technical systems.
  • Ability to engage critically with complex and emerging technologies, including their social, organizational, and ethical implications.

Benefits

  • Thesis work is an excellent way to get closer to Scania and build relationships for the future.
  • Many of today's employees began their Scania career with their degree project.
  • Work closely with experts in AI, product development, and data engineering.
  • Research can directly shape the way we build the future of transportation.
  • Background check might be conducted for this position.

Skills

AIdata sciencecomputer sciencehuman-computer interactionindustrial engineeringautonomous systemscognitive sciencedata engineering
#Scania#TRATON#data ecosystems#AI#resilience#human-in-the-loop#future of transportation#KTH
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About Scania Group

Scania is a world-leading provider of transport solutions committed to a better tomorrow. Our purpose is to drive the shift towards a sustainable transport system. In doing so, we are creating a world of mobility that’s better for business, society and our environment. Employing more than 50,000 people in about 100 countries, Scania’s research and development is concentrated in Sweden, while production takes place in Europe and South America.

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Company

Scania Group

Job Posted

2 days ago

Expires

in 4 weeks

Employment Type

Temporary

Work mode

Hybrid

Experience Level

Entry

Locations

Södertälje, Sweden

Qualification

Master

Applicants

Be an early applicant