Postdoc in Self-Adaptive AI Systems and Embedded Intelligence - DTU Compute

Are you looking to grow your career in intelligent embedded systems, edge computing, and AI-enabled infrastructures?

Join the Embedded Systems Engineering (ESE) research section at DTU Compute, where your expertise in dependable systems, embedded intelligence, and sustainable computing can help shape the next generation of AI-enabled technologies. By joining us, you stand to gain extensive support unlocking your career potential. You'll have access to state-of-the-art facilities and expert assistance with improving your proposal writing skills and feedback on grant applications. We actively facilitate building your professional networks, both within Denmark and the EU. Although teaching is not a formal part of the post; we offer opportunities to build your teaching portfolio and supervise undergraduate and postgraduate students on projects related to your research area.

Responsibilities and qualifications We seek a highly motivated Postdoctoral Researcher 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 theory and systems research, spanning uncertainty-aware AI, runtime adaptation, dependable embedded intelligence, and sustainable AI operation.

You will be responsible for: Conducting cutting‑edge research on reliable, sustainable, and self‑adaptive AI systems for embedded, edge, and distributed computing environments.

Developing novel models, methodologies, and runtime mechanisms for characterizing and controlling uncertainty, reliability, resource consumption, and adaptive behavior in AI‑enabled systems.

Developing proof‑of‑concept implementations and experimentally validating proposed solutions on embedded devices, edge platforms, and distributed computing infrastructures, bridging theoretical advances with practical systems prototyping.

Publishing and disseminating research results in leading international conferences and journals and contributing to collaboration and knowledge transfer with academic and industrial partners.

Supervising MSc and PhD students and contributing to the development of a growing research environment within the ESE section.

You should have: A PhD degree in Computer Science, Electrical Engineering, Applied Mathematics, Machine Learning, or a related field.

Research interests in AI systems, embedded intelligence, edge computing, dependable systems, machine learning, or related areas that can be documented by a publication record in relevant venues.

Strong analytical and mathematical problem‑solving skills.

Experience in experimental systems research and prototype development.

Excellent communication skills in English.

Strong advantages Experience developing experimental prototypes and evaluating AI‑enabled systems on embedded devices, cyber‑physical platforms, or resource‑constrained computing environments.

Experience with probabilistic reasoning, uncertainty‑aware machine learning, statistical modelling, or related techniques for reasoning under uncertainty.

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 terms of employment 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.

Employment period and start date The period of employment is 2 years. The starting date is January 2027 or soon thereafter according to mutual agreement.

Location Kgs. Lyngby, Denmark

EEO statement All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply. As DTU works with research in critical technology, which is subject to special rules for security and export control, open‑source background checks may be conducted on qualified candidates for the position.

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