PhD position in Data-Enhanced Model Discovery for Physical Sciences
1 month ago
Title:
PhD position in Data-Enhanced Model Discovery for Physical Sciences
Research 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.
The distinct feature of our approach is the interpretability of the models discovered using our algorithms, compared to black-box, purely data-driven methods. Also, we combine AI/ML tools with mathematical and physical theories, to guarantee the consistency of the generated models and aim at maximizing their generalization capabilities.
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:
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, (main supervisor)How to apply:
Please follow this link 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 application guide.
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.
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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