PhD position in Data-Enhanced Model Discovery for Physical Sciences
Aarhus Universitet
- Aarhus, Midtjylland
- Permanent
- Fuldtid
PhD position in Data-Enhanced Model Discovery for Physical SciencesResearch area and project description:
Data-driven models are becoming increasingly important in both academia and industry for enhancing simulations of complex phenomena. In this research, supported by the ERC Starting Grant project “ALPS-AI-based Learning for Physical Simulation”, we use machine learning tools and the latest development in AI to discover new models and improve simulators in different fields:
- growth phenomena in natural systems (such as plants and living organisms): we aim at gathering insight into the physics behind the complex growth patterns observed in nature to provide design principles for nature-inspired robots;
- soft robotics: developing accurate and efficient model for continuum soft manipulators is crucial for implementing effective control strategies. We would like to distill these models from experimental data, using our algorithms;
- fluid mechanics: the prediction of complex phenomena such as turbulence requires dedicated modeling approaches that can benefit from data-driven methods.
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:
Applicants to the PhD position must have a relevant Master's degree in Mechanical Engineering, Aerospace Engineering, Electrical Engineering, Control 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, 8000 Aarhus C, Building 3210.Contacts:
Applicants seeking further information are invited to contact:
- Alessandro Lucantonio,
Please follow to submit your application.
Application deadline is 15 May at 23:59 CEST.
Preferred starting date is 1 September 2024.For information about application requirements and mandatory attachments, please see our .Please note:
- Only documents received prior to the application deadline will be evaluated. Thus, documents sent after deadline will not be taken into account.
- 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.