We are recruiting one doctoral researcher (3 years) to the AEGIS network
AEGIS — Adaptive Grid-Interactive Edge Datacenter Fleets — is a European research and training network. It is funded by the EU through a Marie Skłodowska-Curie Doctoral Network, runs from 2026 to 2030, and trains 15 Doctoral Candidates (PhD students). The DN targets developing software-defined technologies that turn edge data centers from passive electrical loads into active, carbon-efficient and grid-interactive resources. The project has three layers:
- A programmable infrastructure layer gives safe, runtime-verified control of a site’s power electronics, cooling, and AI hardware.
- An intelligence layer reads real-time grid signals and turns a request such as “reduce power by 20%” into the detailed actions that hardware and facilities must take, without breaking service.
- A fleet orchestration layer coordinates many sites, even when they have different owners, using trusted and privacy-preserving methods, so the whole fleet can act as one Virtual Power Plant.
Read more about the project and other participants here: https://aegis-dn.eu/
Your role:
You will be working on “End-to-End Energy Modeling for Distributed AI Services”. To make carbon-aware decisions, both orchestrators and developers need to see the real energy cost of an AI workload. In this project you build analytical models and systems that make energy and carbon metrics visible. You will create compositional energy models that span the radio network, the transport network, and the datacenter hardware, and expose them through a fast query interface so any tool can ask, “what does this AI service cost in energy?”
You will be responsible for:
- Developing compositional energy models for disaggregated radio (RAN) components, transport networks, and datacenter hardware.
- Building a low-latency query API that returns the end-to-end energy cost of an AI service.
What you will deliver:
- Validated models with less than 10% prediction error on the Aalto and Ericsson testbeds.
- A query API that returns end-to-end energy-cost estimates in under 100 milliseconds.
- A doctoral dissertation that you will defend.
Secondments:
You will spend two research visits with partners in the network:
- Ericsson (Finland) — 3 months from around May 2028 (industry), with Tomas Mecklin: test the energy models on Ericsson’s infrastructure testbeds.
- TU Wien (Vienna, Austria) — 3 months from around May 2029 (academic), with Ivona Brandić: combine the digital-twin models with the end-to-end energy models.
The position requires:
- Master's degree in computer science, communications engineering, telecommunications, or a related field (with a CGPA of at least 4/5)
- Experience (e.g. coursework, projects, etc.) in AI and machine learning, including understanding of various DNN architectures, training models, and applying them for different tasks
- Understanding of computer and telecom networks (for example RAN)
- Experience with empirical measurements (Prior work on energy or power measurement is strongly preferred)
- Data analysis and analytical modeling — identifying the features that drive system behaviour and building compositional or analytical models from measured data (an interest or aptitude here is enough; we don’t expect prior demonstrated experience)
- Good programming skills – you are required to provide a sample of your code during the recruitment process
- Fluency in written and spoken English. See https://www.aalto.fi/en/study-options/aalto-doctoral-programme-in-electrical-engineering#8-required-language-proficiency for information on how you can demonstrate proficiency in English. This is required when officially applying for doctoral studies at the School of Electrical Engineering in Aalto University (within 6 months after starting in the job). Please note that you do not need official proof when applying for this job.
If you are chosen for this position, you will apply for the study right in doctoral studies at Aalto University School of Electrical Engineering. Thus, please see the student information and admission criteria at https://www.aalto.fi/en/study-options/aalto-doctoral-programme-in-electrical-engineering.
MSCA eligibility
You must meet the following requirements:
- No doctoral degree. At the date of recruitment, you must not yet hold a PhD.
- Mobility rule. You must not have lived or done your main activity (work or studies) in Finland for more than 12 months in the 36 months just before you are recruited, unless as part of a compulsory national service or a procedure for obtaining EU temporary protection or refugee status under the Geneva Convention. Short stays such as holidays do not count.
- All nationalities welcome. The positions are open to applicants of any nationality.
What we offer:
You will become a part of the Cloud and Network Computing group, headed by assistant professor Gopika Premsankar. You will be advised by Riku Jäntti, full professor in Communications Engineering. Both groups are based in the Department of Information and Communications Engineering in the School of Electrical Engineering.
The position starts in March 2027 or as mutually agreed. The start date cannot be later than June 2027. The employment contract will be made for three years.
Application documents
To apply, please share the following application materials (as PDFs) with us through our recruitment site ("Apply now!” at the bottom of the page):
- A CV
- A short letter of motivation, at most 1 page, which describes your interest and motivation (please try to include details that are not part of your CV and emphasize how you address the position-specific requirements listed above)
- Sample code, preferably on a code repository (Provide a URL and describe in one paragraph your role in developing the software)
- Names and email addresses of two reference providers. They will be contacted directly at a later stage in the application process.
- Transcript of grades for your Bachelor’s and Master’s degrees
Please note that our recruitment system allows maximum of 5 attachments, so please combine e.g. the copies of transcripts in one PDF, if necessary.
Application process
The application deadline is December 15, 2026 23.59pm (EET). We will go through the applications in batches, and we may invite suitable candidates to interview already during the application period. The call will be closed early, if the position is filled before the application deadline.
Please note: Aalto University’s employees should apply for the position via our internal HR system Workday (Internal Jobs) by using their existing Workday user account (not via the external webpage for open positions).
More information
For more information about the position, please contact Professor Gopika Premsankar (gopika.premsankar@aalto.fi). For questions about the application process, please contact HR Advisor Johanna Haapalainen at hr-elec@aalto.fi.
Why Finland and why this group
Aalto University provides a vibrant and collaborative environment. We work in a hybrid way, and the primary workplace is Otaniemi, Espoo. The Otaniemi campus is a thriving and connected community of 100 nationalities, 16,000 students and 5,200 employees. Life at the campus is vibrant and filled with amazing architecture, calming nature, and a variety of cafes, restaurants, services and good transport connections.
Finland is a great place for living – it is a safe, politically stable and well-organized Nordic society. For more information about living in Finland: https://www.aalto.fi/en/careers-at-aalto/living-in-finland & https://www.aalto.fi/en/services/welcome-to-aalto-university-and-finland-info-package
Read more about working at Aalto: https://www.aalto.fi/en/careers-at-aalto and check out our new virtual campus experience: https://virtualtour.aalto.fi
More about Aalto University:
Aalto.fi
youtube.com/user/aaltouniversity
linkedin.com/school/aalto-university/
www.facebook.com/aaltouniversity
instagram.com/aaltouniversity
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