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PhD scholarships in machine learning for optimization of cyber-physical systems - DTU Compute

DTU97 open roles

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Kgs. Lyngby, Denmark
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Your applicationOpen nowPhD scholarships in machine learning for optimization of cyber-physical systems - DTU ComputeDTU · Kgs. Lyngby, Denmark

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The clock on this job

Early applications get read.

13.7% of postings close within 7 days. Measured by our own scanner across the market. DTU postings stay open a median of 17 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 13.7%7 days
  4. 22.1%14 days
  5. 37.8%30 days
  6. 59.1%60 days
This job: posted today

DTU median: 17 days open

The posting

Job Description

We offer PhD scholarships at DTU Compute to develop machine learning methods for faster analysis and optimization of cyber-physical systems. You will build predictive models of expensive analytical calculations and simulations, and use AI to find good solutions to optimization problems that cannot be solved exactly within practical computing budgets.

You will join the Embedded Systems Engineering section and work with Prof. Paul Pop. The application areas are related to, e.g., software-defined vehicles, datacenters, industrial automation, and energy systems.

Responsibilities and qualifications

Your research will connect learned prediction models with optimization methods. The PhD topics will be defined with the supervisors. You will:

  • Develop surrogate models that predict results of complex analyses and simulations, such as execution delays, energy use, and resource demands.
  • Use machine learning to guide configuration, scheduling, and resource allocation, reducing the need for expensive model evaluations.
  • Evaluate solution quality, computing time, uncertainty, and transfer to new systems; check proposed solutions against the original models and constraints.
  • Publish your research, collaborate with project partners, and contribute to teaching and student supervision.

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.

Ideally, you have both a BSc and an MSc in machine learning or artificial intelligence. Degrees in computer science, applied mathematics, electrical engineering, or related fields with substantial ML/AI coursework and projects are also relevant.

You should have a strong foundation in machine learning, algorithms, probability, and linear algebra; experience implementing and evaluating models in Python; and good written and spoken English. Experience with optimization, reinforcement learning, or simulation is an advantage. Prior expertise in all application areas is not required.

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.

Assessment

Assessment will consider academic qualifications, machine learning and programming experience, research potential, and fit with the topic.

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.

At DTU Compute, we have a large focus on creating a good working environment. Our work with diversity and inclusion is an essential part of that. We believe that having a good working environment is a necessary foundation to provide excellent research, teaching, supervision and innovation.

At DTU Compute, we have about 140 PhD students. We offer several events and activities for all our PhD students such as annual PhD Bazaar, onboarding course where you will meet other PhD students, and you can join our PhD Club that organizes BBQs, board games events, lunches etc.

You can read more about DTU Compute at www.compute.dtu.dk

Salary and appointment terms

The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. Please see DTU’s salary structure for scientific staff: www.inside.dtu.dk/en/human-resources/during-employment/salary/salary-structures

The period of employment is 3 years. Starting date is January 1, 2027, or according to mutual agreement. Both positions are full-time.

You can read more about career paths at DTU here.

Further information

Further information may be obtained from Prof. Paul Pop ([email protected]) and Associate Prof. Silviu Craciunas ([email protected])

You can read more about 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 24 November 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
  • An example of your technical writing and a code sample or repository link, with a short explanation of your contribution

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

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 at DTU Compute develops methods and tools for embedded, distributed, and cyber-physical systems, including real-time analysis, optimization, and communication.

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 here: 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.

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