About the opportunity
The Embedded Systems Engineering (ESE) research section at DTU Compute is offering a Marie Skłodowska-Curie (MSCA) PhD fellowship under the MSCA Doctoral Network AEGIS (Adaptive Grid-Interactive Edge Datacenter Fleets). The research topic focuses on ‘Carbon-Aware Neural Architecture Search (NAS)’ to pioneer AI models capable of trading accuracy for lower energy and carbon consumption at runtime based on power grid status. The PhD position spans three years starting in April 2027 or by mutual agreement, and includes two funded 3-month industry secondments at TDC NET (Denmark) and Dell Technologies (Ireland).
Salary and benefits
- Competitive living allowance (salary), mobility allowance, and family allowance (if eligible)
- 3-year full employment period under the collective agreement with the Danish Confederation of Professional Associations
- Two 3-month funded industry secondments at TDC NET (Denmark) and Dell Technologies (Ireland)
- Participation in a network-wide training program within the AEGIS MSCA Doctoral Network
Who can apply?
- Must hold a two-year MSc degree (120 ECTS or equivalent) in Computer Science, Electrical Engineering, Machine Learning, Applied Mathematics, or a related field
- Applicants may apply prior to receiving their master's degree, but must have obtained it before starting
- Must not already hold a doctoral degree at the date of recruitment
- Mobility rule: Must not have resided or carried out main activity (work or studies) in Denmark for more than 12 months in the 36 months immediately preceding recruitment
- Strong background in AI systems, embedded intelligence, edge computing, or machine learning
- Strong analytical and mathematical problem-solving skills, programming experience, and experimental system evaluation skills
- Excellent communication skills in English
Required documents
- Cover letter motivating the application
- Curriculum vitae (CV)
- Grade transcripts and BSc/MSc diplomas in English, including official description of the grading scale
- Links to relevant public code repositories, software artifacts, datasets, or research prototypes (if available)
- Additional optional material demonstrating research experience (publications, thesis work, or research projects)
- Contact information for up to two references
- Note: All application materials must be submitted in English compiled into a single PDF file
When to apply
- Application deadline: October 4, 2026, at 23:59 Danish time
- Expected position start date: April 2027 or soon thereafter
How to apply
- Click on 'Apply Now' on the official DTU job posting page
- Fill out the online application form
- Upload all required application documents in English merged into one single PDF file
- Submit the application prior to the deadline on October 4, 2026 (23:59 Danish time)
Additional information
- The PhD scholarship is subject to academic approval and candidate enrolment in a PhD program at DTU
- As DTU conducts critical technology research, open-source background checks may be performed for qualified candidates
- Enquiries may be directed to Professor Xenofon Fafoutis (xefa@dtu.dk) or Associate Professor Luca Pezzarossa (lpez@dtu.dk)
Our Take on This Opportunity
This section reflects Open Opportunities’ own analysis of the opportunity from an applicant’s perspective.
You may be a strong fit if…
- Master's degree in Computer Science, Electrical Engineering, or Machine Learning.
- Strong background in AI systems, edge computing, or embedded intelligence.
- Must meet the MSCA mobility rule: not having resided in Denmark for more than 12 months in the last 3 years.
What should you think carefully about?
- The position is on-site at DTU Compute, requiring relocation to Denmark.
- The role includes two mandatory 3-month industry secondments in Denmark and Ireland.
- Applicants must not already hold a doctoral degree.
How could this fit your current goals and plans?
This MSCA fellowship is a prestigious, well-funded path for an early-career researcher to gain both academic and industrial experience. By working on carbon-aware AI, you will develop highly relevant skills in sustainable computing that are increasingly critical in both the tech industry and academia.
Our take
An excellent, highly competitive fellowship for early-career researchers who want to combine academic PhD studies with direct industry exposure in the field of sustainable AI.
Ready to apply?
Review the opportunity on the official website before applying.
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