Contrato doctoral Universidad de Aberdeen (Reino Unido) - 3 años

Research Focus: Physics-Informed Neural Networks for control of compliant robotic systems

Job description:
We are seeking a highly motivated PhD candidate to join our interdisciplinary Artificial intelligence, Robotics and Mechatronic Systems Group (ARMS), to advance the modelling and control of complex, compliant robotic systems using Physics-Informed Neural Networks (PINNs).

This research aims to address critical challenges in the control of unconventional robots, such as soft and origami
robots, that require innovative control techniques to manage their complex dynamics, nonlinear behaviours, and interactions with changing environments.

The focus of this work is the development of robust, safe, and resilient control methodologies for compliant robotic systems. Specifically, this research will apply and extend PINNs for modelling and controlling these robots under
conditions where external perturbations (e.g., unpredictable environmental interactions, variable loads, and force disturbances) may impact performance.

The candidate will work on combining PINN-based learned models with traditional model-based controllers, often developed from first principles, to achieve precise, adaptable, and resilient performance in complex robotic systems. By merging established and novel control methods, the project aims to ensure both theoretical stability and practical robustness for compliant robots that are safe to interact with people and adaptable to environmental changes.

This research will advance both the theore:cal and practical aspects of control in compliant robotics, resulting in breakthrough methodologies for creating resilient, safe, and adaptable robots. This project offers an exciting opportunity to make impactful contributions in the fields of robotics, machine learning, and control engineering.

Your profile:

• A First-Class Bachelor’s or Master’s Degree (preferred) in Robotics, Mechanical Engineering, Computer Science, Electrical Engineering, Physics, Applied Mathema:cs or a related field.
• Prior experience in working with mathema:cal models of dynamical systems or neural network architectures is highly desirable, as is familiarity with partial differen:al equations (PDEs) and their numerical solution methods.
• Proficiency in at least one programming language / soMware package commonly used for scientific computing (MATLAB / Python / C).
• Solid understanding in control theory and its application to robotics

Our offer:

• Full International Postgraduate Research Student Fees for 3 years and an annual tax-free stipend at the current UK rate (currently £19,237 with an annual inflation-related increase).
• An inspiring multidisciplinary, international, and academic environment.
• The university offers a dynamic ecosystem with enthusiastic colleagues in which internationalization is an important part of the strategic agenda.
• A professional and personal development program within University of Aberdeen.
• Excellent support for research and facilities for professional and personal development.
• Excellent working conditions, an exciting scientific environment, and a green and lively campus.

Information and application
For more information about the position, you can contact Prof. Sumeet S. Aphale (email: s.aphale@abdn.ac.uk). You are also invited to visit our homepage.
For questions about living in Aberdeen please consult the website of the university: https://www.aberdeen-isc.ac.uk/international-study-centre/living-in-aberdeen.
Please submit your applica:on before December 31st, 2024. Potential candidates are requested not to use LLM tools (e.g. ChatGPT) to write their application. Your application should include:

• A cover letter with your favourite programming language (and why) to prove that you have read the full vacancy text, applications without such explanation will not be considered.
• Curriculum Vitae with a description of relevant academic/professional achievements, and at least two references with their contact details.
• An academic transcript of your Undergraduate (Bachelors) and Postgraduate (Masters) education, including grades.
• Abstract and first two pages of your most recent academic report (thesis/final project report) to serve as an academic writing sample.
• A statement of research for this position, where you should explicitly mention scientific gaps that you would like to focus your research on.
• The interviews will be held after the second week of January 2025 with an aim to have the candidate start as soon as possible and no later than October 2025.