项目介绍

2026年7月2日

If you wish to pursue your career at the interface of mechanical engineering and machine learning, DTU Engineering Technology at the Technical University of Denmark invites applicants for a 3-year PhD position on physics-enforced machine learning for flow field and heat transfer prediction from limited data. The position is affiliated with the Section for Mechanical Technology and will be under the supervision of Associate Professor Ioanna Aslanidou. The project focuses on applied research to develop methodologies for incorporating physics into machine learning models for flow prediction. A key challenge is to build trust in the model so that it can be used for industrial applications where accuracy and reliability are paramount. A fast and reliable model can enable multiple industrial applications from assessing designs of new systems to optimal control of energy-intensive industrial processes and contribute to building sustainable energy and manufacturing systems.

As part of the project, you will develop as a researcher, deepen your technical and professional skills, and explore the interdisciplinary nature of the research area. You will build a network, collaborate with academia and industry, and disseminate your research at international conferences. 

You will join a cross-disciplinary team of researchers focusing on mechanical engineering, fluid dynamics, materials science, and control systems. Our section is diverse in nationalities, personality types, and career paths. We enjoy collegial idea generation, feedback and cooperation in an informal and trustful working environment as well as social activities together outside of working hours.

Responsibilities and qualifications
We seek a motivated, ambitious, and curious engineer interested in narrowing the gap between machine learning/black box models and physics-based models for fluid mechanics and heat transfer applications and working on problems relevant to industry. For this project, you should have prior experience with fluid mechanics and modelling. Your primary responsibilities will include:

• Explore techniques to develop fast and reliable machine learning models incorporating physics for flow and heat transfer prediction from limited data
• Perform CFD simulations and use datasets for model training, validation, and benchmarking
• Design and validate physics-informed neural network (PINNs) and alternative architectures for flow and heat transfer prediction for industrial applications

Active dissemination of the results in scientific articles and participation in national and international conferences is integral to the job. Furthermore, participation in supervising B.Eng., B.Sc., and M.Sc. students is expected. This project also involves a research stay abroad and you are expected to engage and collaborate with both academic and industrial partners in Denmark as well as abroad.

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. 

The ideal candidate has a mechanical engineering background with a focus on fluid mechanics and heat transfer in industry-relevant applications or equivalent experience and a few of the following:

• Experience in machine learning and/or programming e.g. using Python
• Experience in computational modelling for fluid mechanics
• Experience in mathematical modelling

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. 

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 appointment terms 
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 3 years. The expected starting date is 01 October 2026. The position is a full-time position.

You can read more about career paths at DTU here.

Further information
Further information may be obtained from Associate Professor Ioanna Aslanidou (ioaas@dtu.dk) or the head of the section, Associate Professor Christian Kim Christiansen (chkch@dtu.dk).

You can read more about DTU Engineering Technology at www.engtech.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 15 July 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

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.