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Technical University of Denmark

Just Landed

PhD Scholarship in Machine Learning for Optimization of Cyber-Physical Systems Technical University of Denmark in Denmark

Degree Level

PhD

Field of study

Computer Science

Funding

This is a full-time, three-year PhD appointment with salary and appointment terms governed by the collective agreement with the Danish Confederation of Professional Associations. The posting does not state a specific salary amount or separate tuition coverage.

Deadline

Nov 24, 2026

Country flag

Country

Denmark

University

Technical University of Denmark

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Keywords

Computer Science
Artificial Intelligence
Reinforcement Learning
Monte Carlo Simulation
Resource Allocation
Job Scheduling
Optimisation
Surrogate Modeling
Embedded System
Cyber-physical System
ML

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Posted Yesterday

About this position

DTU Compute is offering a PhD scholarship focused on developing machine-learning methods for faster analysis and optimization of cyber-physical systems. The project will connect learned prediction models with optimization methods to address analytical calculations and simulations that are too expensive to evaluate repeatedly within practical computing budgets.

The PhD researcher will develop surrogate models for predicting outputs such as execution delays, energy use, and resource demands. Machine learning will then be used to guide configuration, scheduling, and resource-allocation decisions while reducing reliance on costly model evaluations. The work will also assess solution quality, computing time, uncertainty, and transferability to new systems, with proposed solutions checked against original models and constraints.

The research is situated in the Embedded Systems Engineering section at DTU Compute and will be conducted with Professor Paul Pop and Associate Professor Silviu Craciunas. Potential application areas include software-defined vehicles, datacenters, industrial automation, and energy systems. The environment brings together research in embedded, distributed, and cyber-physical systems, including real-time analysis, optimization, and communication.

The doctoral researcher will publish research, collaborate with project partners, and contribute to teaching and student supervision. DTU Compute provides an international research setting with a substantial PhD community, academic events, onboarding activities, and a PhD club.

Funding details

This is a full-time, three-year PhD appointment with salary and appointment terms governed by the collective agreement with the Danish Confederation of Professional Associations. The posting does not state a specific salary amount or separate tuition coverage.

What's required

Applicants must hold a two-year master's degree (120 ECTS) or an equivalent qualification at the same academic level. A BSc and MSc in machine learning or artificial intelligence are preferred; degrees in computer science, applied mathematics, electrical engineering, or related fields with substantial machine-learning or AI coursework and projects are also relevant. Candidates 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 advantageous. Applicants may apply before completing their master's degree but cannot begin until it has been awarded. Assessment considers academic qualifications, machine-learning and programming experience, research potential, and fit with the topic.

How to apply

Submit the complete online application through the “Apply now” portal by 24 November 2026 at 23:59 Danish time. Upload one PDF in English containing a motivation letter, CV, grade transcripts and BSc/MSc diploma with the official grading-scale description, plus a technical-writing example and code sample or repository link with a short explanation of your contribution.

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