Meet ApplyKite Twin, the application assistant that learns with you
Meet your Twin, it learns with you
Your Twin learns with you
Launch week codes:30% off annual Pro20% off monthly Pro
Ends in00h00m00s
Ends in00h00m00s
Paul Pop
Just Landed
New Today
PhD scholarships in machine learning for optimization of cyber-physical systems Technical University of Denmark in Denmark
Degree Level
PhD
Field of study
Computer Science
Funding
PhD scholarships at DTU with appointment for 3 years under the collective agreement with the Danish Confederation of Professional Associations; salary follows DTU's salary structure for scientific staff.
Deadline
Nov 24, 2026
Country
Denmark
University
Technical University of Denmark
Apply for this scholarship
Keywords
Suggested scholarships
About this position
DTU Compute is offering PhD scholarships in machine learning for the optimization of cyber-physical systems. The project focuses on developing learning-based methods that can speed up analysis and improve the optimization of systems where exact solutions are too costly to compute in practice.
The selected PhD student will work in the Embedded Systems Engineering section at the Technical University of Denmark and join a research environment centered on embedded, distributed, and cyber-physical systems. The research direction combines predictive modelling with optimization: building surrogate models for expensive analytical calculations and simulations, then using AI-driven methods to search for good configurations and decisions under practical computing constraints.
Research problems mentioned in the advert include predicting quantities such as execution delays, energy use, and resource demand; guiding configuration, scheduling, and resource allocation; and assessing solution quality, uncertainty, transferability, and agreement with original models and constraints. Application contexts include software-defined vehicles, datacenters, industrial automation, and energy systems, giving the project a broad but clearly systems-oriented character.
The PhD topics will be defined together with the supervisors. The position is embedded in a department with a large PhD community and an international research culture, and students are expected to publish, collaborate with project partners, and contribute to teaching and student supervision. The advert also highlights the broader DTU Compute environment, which combines research in mathematics, data science, computer science, and computer engineering with work on AI, machine learning, IoT, cybersecurity, and related digital technologies.
Supervision is provided by Prof. Paul Pop and Associate Prof. Silviu Craciunas.
Funding details
PhD scholarships at DTU with appointment for 3 years under the collective agreement with the Danish Confederation of Professional Associations; salary follows DTU's salary structure for scientific staff.
What's required
Applicants must have a two-year master's degree (120 ECTS) or an equivalent degree at the same academic level. Ideally, candidates 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. Applicants 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.
How to apply
Submit the complete online application via the Apply now link. Upload all materials as one PDF in English, including a cover letter, CV, transcripts and BSc/MSc diploma, and an example of technical writing plus a code sample or repository link with a short explanation. Apply by 24 November 2026 at 23:59 Danish time; late applications will not be considered.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the provider.
Professors
Prof. at Technical University of Denmark
Denmark
Research Interests
Internet Of Things
Cloud Computing
Networking
Real-time Systems
Cyberinfrastructure
Associate Prof. at Technical University of Denmark
Denmark
Research Interests
Mathematics
Job Scheduling
Monte Carlo Simulation
Computer Science
Resource Allocation
Make your next move.
Prepare your application
Review drafts and confirm requirements with the provider.