PhD position in Machine Learning and Physical Simulation

at Aarhus University
Published February 8, 2023
Location Aarhus, Denmark
Category Machine Learning  
Job Type Scholarship  


Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Mechanical and Production Engineering programme. The position is available from 15 May 2023 or later.
PhD position in Machine Learning and Physical Simulation

Research area and project description:
Over the last decades, Artificial Intelligence (AI) and Machine Learning (ML) methods have successfully entered science and engineering workflows to match the growing demands for fast and accurate physical models. However, purely data-driven methods often fail to generalize to new scenarios and produce results based on policies that are hard to interpret.

To overcome these limitations, the ERC Starting Grant project ALPS – AI-based Learning for Physical Simulation proposes an original approach combining ML methods, such as neural networks, genetic algorithms and reinforcement learning, and discrete mathematical theories, such as graph theory, discrete exterior calculus, and discrete differential geometry, for the development of new algorithms that can automatically learn models of physical systems from experimental data. To tackle the associated computational, the algorithms will be implemented in a new software library exploiting state-of-the-art high-performance computing techniques.

The methods proposed in this project will be applied to address scientific challenges in human health, sustainable energy science and technology, and soft robotics. In particular, we envision the development of new effective models of tumor growth, where accurate mathematical models are still elusive and could provide the basis for new treatment strategies. Further, we will use the algorithms to derive effective reduced-order models for model-based control in soft robotics and to tackle design, optimization, and control problems in engineering for sustainable energy technology, in collaboration with industries.

The successful candidate will work on: 1) the definition of a computational framework that combines model learning and simulation of physical systems; 2) the implementation of high-performance algorithms and their application to the aforementioned scientific challenges.

Project description. For technical reasons, you must upload a project description. Please simply copy the project description above, and upload it as a PDF in the application.

Qualifications and specific competences:
Master’s degree in Physics, Mechanical Engineering, Aerospace Engineering, Electrical Engineering, Electronic Engineering, Computer Science, Data Science, Artificial Intelligence.

Place of employment and place of work:
The place of employment is Aarhus University, and the place of work is Inge Lehmanns Gade 10, building 3210

Applicants seeking further information are invited to contact:
Associate Professor Alessandro Lucantonio,

How to apply:
Please follow this link to submit your application. Application deadline is 15 March 2023 23:59 . Preferred starting date is 15 May or soon after.

For information about application requirements and mandatory attachments, please see our application guide.

Please note:

  • The programme committee may request further information or invite the applicant to attend an interview.
  • Shortlisting will be used, which means that the evaluation committee only will evaluate the most relevant applications.

Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants. All interested candidates are encouraged to apply, regardless of their personal background. Salary and terms of employment are in accordance with applicable collective agreement.  

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