2026 PhD Software Engineering Internship, Aarhus
UberAarhus, DenmarkPosted 5 March 2026
Job Description
2026 PhD Software Engineering Internship, Aarhus
Department: University
Team: Engineering
Location: Aarhus, Denmark
Type: Intern
## **About the team:**
Uber Denmark is the powerhouse behind the core infrastructure that runs Uber globally. We don’t just build mobile apps; we build the systems that deploy and run every microservice, database, and data workload across the world. For a PhD intern, this means your research isn't destined for a shelf, it’s destined for production at a scale few companies can match.
You will be embedded in a team of specialists to tackle bold, unsolved problems in computer science. As a PhD intern, you will own a project from ideation to implementation, with the explicit goal of bridging the gap between novel research and production impact. You’ll work alongside a concentrated group of PhDs and engineers in Aarhus who speak your language, providing a high-caliber peer group that understands how to translate academic rigor into industry-shaping technology.
**About the Role:**
This role is for the PhD student who thrives in the gap between "theoretically possible" and "operationally reliable." You will join a stellar team of engineers in Aarhus, including several with PhDs, where you will solve high-stakes problems in reliability and efficiency. The challenge is real: our systems are massive, the pace is relentless, and the data is often messy. You’ll need more than just technical depth; you’ll need the grit to navigate ambiguity, the ownership to see a project through to implementation, and the adaptability to pivot when real-world constraints clash with your initial hypothesis. If you are motivated by seeing your algorithms and models directly impact millions of users, this is where you belong.
## **Example projects ( _you’ll focus on one primary project)_:**
- Optimize bin packing in our dynamic environment to increase host utilization rates, reducing global infrastructure costs.
- Build a code risk scoring model that predicts the likelihood of a code change causing a production incident, helping us block high-risk changes before they land.
- Navigate the mes
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