项目介绍

2026年8月13日

Are you interested in pursuing a PhD at the intersection of artificial intelligence, embedded systems, and sustainable computing? 

Join the Embedded Systems Engineering (ESE) research section at DTU Compute and contribute to research on the next generation of reliable and self-adaptive AI-enabled systems. 

As a PhD student at DTU, you will work in an international and collaborative environment with access to state-of-the-art facilities and opportunities to engage with leading academic and industrial partners.

Responsibilities and qualifications
We offer a PhD scholarship to contribute to the REGAIN-AI project, a newly established research initiative investigating reliability, sustainability, and self-adaptation in next-generation AI-enabled systems. Funded by the Novo Nordisk Foundation, this project explores how uncertainty introduced by generative AI components can be characterized, bounded, and controlled in embedded, edge, and distributed computing environments.

Recent advances in large language models and generative AI are enabling increasingly autonomous systems across the computing continuum, from embedded devices to cloud infrastructures. However, integrating probabilistic AI components into traditionally deterministic systems introduces new challenges related to uncertainty, reliability, and resource consumption, particularly in resource-constrained environments. REGAIN-AI aims to develop foundational models and system mechanisms for understanding, bounding, and controlling these effects.

The project combines theoretical research with hands-on experimental validation, including the development and evaluation of AI-enabled systems on embedded, edge, and distributed computing platforms. You will have the opportunity to work on both fundamental and practical aspects of next-generation AI systems.

The position is part of a growing research effort in AI-enabled systems, and you will work closely with postdoctoral researchers and other collaborators within the project in an international and interdisciplinary research environment.

You will be responsible for:

• Conducting research on reliable, sustainable, and self-adaptive AI systems for embedded, edge, and distributed computing environments.
• Developing models, methodologies, and runtime mechanisms for characterizing and controlling uncertainty, reliability, resource consumption, and adaptive behaviour in AI-enabled systems.
• Developing proof-of-concept implementations and experimentally validating proposed solutions on embedded devices and distributed computing infrastructures.
• Publishing and disseminating research results in international conferences and journals.
• Contributing to the department with service work, including being a Teaching Assistant.
• Contributing to a collaborative research environment and participating in interactions with academic and industrial partners.

You should have:

• A MSc degree in Computer Science, Electrical Engineering, Machine Learning, Applied Mathematics, or a related field.
• A strong academic background and interest in AI systems, embedded intelligence, edge computing, machine learning, dependable systems, or related areas.
• Strong analytical and mathematical problem-solving skills.
• Experience with programming and experimental evaluation of computing systems.
• Excellent communication skills in English.

The following qualifications are considered strong advantages:

• Experience developing software prototypes or conducting experimental evaluations on embedded devices, cyber-physical systems, or resource-constrained computing platforms.
• Experience with machine learning, probability theory, statistical modelling, or related topics.
• Previous research experience, demonstrated through publications, thesis work, research projects, or similar activities.

You must have a two-year master’s degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master’s degree.

Approval and Enrolment 
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU’s rules for the PhD education. 

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. 

The period of employment is 3 years. The starting date is 1 January 2027 or soon thereafter according to mutual agreement.

You can read more about career paths at DTU here.

Further information
Further information may be obtained from Associate Professor Roberto Morabito and Professor Xenofon Fafoutis.

You can read more about ESE at www.compute.dtu.dk/sections/emsys and DTU Compute at www.compute.dtu.dk/.

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark. Furthermore, you have the option of joining our monthly free seminar “PhD relocation to Denmark and startup “Zoom” seminar” for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU. 

Application procedure 
Your complete online application must be submitted no later than 21 October 2026 (23:59 Danish time). Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link “Apply now”, fill out the online application form, and attach all your materials in English in one PDF file. The file must include:

• A letter motivating the application (cover letter)
• Curriculum vitae 
• Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale
• Links to relevant public code repositories, software artifacts, datasets, or research prototypes (if available)
• Additional material demonstrating previous research experience, such as publications, thesis work, research projects, or similar activities (optional)
• Contact information for up to two references

You may apply prior to ob­tai­ning your master’s degree but cannot begin before having received it.