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Marie Skłodowska-Curie PhD fellowship in Learning and Optimization Algorithms for Carbon-Aware Datacenter Fleets - DTU Compute

Danmarks Tekniske Universitet (DTU) Kgs. Lyngby, Denmark Posted 4 Sept 2026 DTU CareersTemporaryStudent / internEnglish
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Summary

The PhD candidate will develop algorithms and software for coordinating datacenter workloads and power use in response to live grid signals. The role includes research, collaboration with network partners, and teaching assistance.

Read by AI
Read from the job ad by AI. The employer's own fields always win.

Opportunity summary

A Marie Skłodowska-Curie PhD fellowship is available in the Embedded Systems Engineering (ESE) section at DTU Compute. You will be one of the 15 Doctoral Candidates (DCs) of the MSCA Doctoral Network AEGIS, Adaptive Grid-Interactive Edge Datacenter Fleets, which Prof. Paul Pop, DTU, coordinates together with 10 partners across Europe. This is a software and algorithms project.

You will design algorithms and build software that decide where AI workloads run and when datacenter sites change their power use, so that hundreds of separate sites act as one carbon-efficient grid resource.

The project does not involve electronics, FPGAs, or low-level embedded development, and it does not require prior knowledge of datacenters or energy systems: with a strong background in algorithms and data structures, you can learn the optimization methods and the domain during the PhD. Marie Skłodowska-Curie fellowships are among the most respected and best-paid PhD positions in Europe.

AEGIS sits where two fast-growing fields meet: datacenters and AI infrastructure on one side, energy and power systems on the other. Few people can work across both, so the skills you build here are scarce and in high demand. Our graduates will be ready for roles at cloud and datacenter operators, energy companies, grid operators, telecom companies, and in academia1 …

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