Postdoc in Self-Adaptive AI Systems and Embedded Intelligence - DTU Compute at Danmarks Tekniske Universitet

Kongens Lyngby, Capital Region of Denmark, Denmark -

Full Time

Start Date

Immediate

Expiry Date

30 Sep, 26

Salary

0.0

Posted On

02 Jul, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Embedded Intelligence, Edge Computing, Self-Adaptive AI Systems, Machine Learning, Probabilistic Reasoning, Experimental Systems Research, Prototype Development, Statistical Modelling, Distributed Computing, Dependable Systems, Analytical Problem Solving, English Communication

Industry

Research Services

Description

Are you looking to grow your career in intelligent embedded systems, edge computing, and AI-enabled infrastructures? Join the Embedded Systems Engineering [https://www.compute.dtu.dk/sections/emsys] (ESE) research section at DTU Compute [https://www.compute.dtu.dk/], 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. The project offers significant opportunities to shape emerging research directions, collaborate across disciplines, and contribute to establishing a new research agenda at the intersection of AI systems, embedded intelligence, and self-adaptive computing. 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. The following qualifications are considered 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. The period of employment is 2 years. The starting date is January 2027 or soon thereafter according to mutual agreement. You can read more about career paths at DTU here [http://www.dtu.dk/english/about/job-and-career/working-at-dtu/career-paths]. Further information Further information may be obtained from Associate Professor Roberto Morabito [romor@dtu.dk] and Professor Xenofon Fafoutis [xefa@dtu.dk]. You can read more about ESE at www.compute.dtu.dk/sections/emsys [https://www.compute.dtu.dk/sections/emsys] and DTU Compute at www.compute.dtu.dk/ [https://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 [https://www.dtu.dk/english/about/job-and-career/moving-to-denmark]. Application procedure Your complete online application must be submitted no later than 31 August 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: * Application (cover letter) * CV * Academic Diplomas (MSc/PhD – in English) * List of publications * Links to relevant public code repositories, software artifacts, datasets, or research prototypes (if available) * Contact information for up to three references Applications received after the deadline will not be considered. 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. Embedded Systems Engineering (ESE) [https://www.compute.dtu.dk/sections/emsys] is one of the 10 research section of DTU Compute. Our mission encompasses the creation of insights that allow the development of context-aware, distributed, and embedded cyber-physical systems, with a particular focus on Internet-of-Things (IoT) and the computing continuum eras. Our vision is to pioneer advancements in high-tech distributed and embedded systems technology, driving change, and contributing positively to society. We strive for a future where our research and innovations form the cornerstone of technological advancements, and we're excited to include more brilliant minds in our journey. See our publications [https://orbit.dtu.dk/en/organisations/embedded-systems-engineering/publications/] and projects [https://orbit.dtu.dk/en/organisations/embedded-systems-engineering/projects/] here. DTU Compute – Department of Applied Mathematics and Computer Science – is an internationally recognised academic environment with over 400 employees and 10 research sections. We broadly cover digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted in basic research and centres on mathematical models of the physical and virtual world, as a basis for the analysis, design, and implementation of complex systems. We focus on ensuring that our research results contribute to creating a better society by supporting areas such as health, green transition, energy supply, and life science. We collaborate with universities, public and private organisations, and companies in Denmark and abroad, and through DTU’s startup ecosystem, we encourage innovation and entrepreneurship. We have a strong ethical, human, and sustainable approach that ensures integrity in our work. Therefore, we strive for and take responsibility for driving the democratisation of digital technologies, so that everyone has the opportunity to actively participate in the development, and we ensure a continued open, democratic, and inclusive society for the benefit of all. At DTU Compute, we value diversity, inclusion, and a flexible work-life balance. Read more about us at www.compute.dtu.dk [http://www.compute.dtu.dk]. DTU – For the benefit of society since 1829 DTU is one of Europe's leading elite technical universities. Through research and education at an international top level, we create solutions to the major societal challenges of our time and help secure Europe's global leadership in sustainable technological development. Since Hans Christian Ørsted founded DTU almost 200 years ago, our mission has remained the same: We develop and create value through the natural and technical sciences for the benefit of society. DTU has 13,800 students, 1,600 PhD students, and 6,500 employees. We work in an international environment and have an inclusive, stimulating, and informal work culture. DTU has campuses in all parts of Denmark and in Greenland and collaborates with the best universities around the world.

Responsibilities

Conduct research on reliable, sustainable, and self-adaptive AI systems for embedded and edge computing environments. Develop and experimentally validate novel models and runtime mechanisms to control uncertainty and resource consumption in AI-enabled systems.