PhD Position in machine learning for nonlinear dynamical systems

24 May 2023
Job Information

Organisation/Company

Delft University of Technology (TU Delft)

Research Field

Technology

Researcher Profile

First Stage Researcher (R1)

Country

Netherlands

Application Deadline

20 Jun 2023 - 21:59 (UTC)

Type of Contract

Temporary

Job Status

Not Applicable

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

We are excited to announce a fully funded Ph.D. position financed by the European Pathfinder grant EMERGE (https://eic-emerge.eu/ ), providing a unique opportunity for aspiring researchers.

Combining the power of (deep) learning with the rich theoretical framework of nonlinear dynamical systems holds tremendous potential for advancing our understanding of complex phenomena. By seamlessly integrating these two fields, we can unlock novel insights into the dynamics, patterns, and emergent behavior observed in various domains. A Ph.D. position in this cutting-edge research area offers an exceptional opportunity to contribute to the forefront of scientific discovery and shape the future of artificial intelligence and dynamic systems theory.

This position will be dedicated to exploring the realm of low-dimensional models within the context of high-dimensional dynamical systems, encompassing areas such as soft robots, natural and artificial swarms, and opinion dynamics, among others. The selected student will delve into two key aspects: learning models that accurately describe these complex systems and generating systems that exhibit behavior consistent with given low-dimensional models. Our approach will combine cutting-edge techniques, including deep learning, symbolic regression, and insights from nonlinear dynamical systems, forging new pathways at the intersection of these fields. As a Cosimo Della Santina's group member, the Ph.D. candidate will be part of a collaborative and dynamic research environment. The group's portfolio spans diverse domains, ranging from abstract topics like nonlinear control theory, dynamics, and machine learning to practical applications in agriculture robotics, control of fluids, and healthcare. Within this vibrant setting, the candidate will collaborate closely with a dedicated team of two other Ph.D. students and one postdoctoral researcher, all committed to the success of the EMERGE project.

Requirements
Specific Requirements

The ideal candidate for this position should possess the following qualifications. However, we encourage you to submit your application even if you don't meet all the requirements. Nobody is perfect!

• MSc. degree in machine learning, control theory, applied mathematics, physics, robotics, mechanical engineering, or a closely related field.
• Strong background in either nonlinear dynamics or machine learning, with at least a basic knowledge of the other.
• Proficiency in mathematics.
• Proficiency in using Matlab and Python.
• Excellent written and oral communication skills in English. Non-native speakers can demonstrate their proficiency through IELTS or TOEFL scores or by completing a master's program taught entirely in English*.
• Candidates from under-represented groups are particularly encouraged to apply.

* Please note that proving your fluency in English in the mentioned ways is a firm requirement for all Ph.D. candidates at TU Delft, although it is not necessary at the time of application.

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements .

Additional Information
Benefits

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2541 per month in the first year to € 3247 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged.

For international applicants, TU Delft has the Coming to Delft Service . This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme for partners and they organise events to expand your (social) network.

Selection process

Are you interested in this vacancy? Please apply by June 20, 2023 via the application button and upload your motivation and CV.

A pre-employment screening can be part of the selection procedure.

You can apply online. We will not process applications sent by email and/or post.

Please do not contact us for unsolicited services.

Additional comments

For more information about this vacancy, please contact Dr. C. (Cosimo) Della Santina, [email protected] .

Website for additional job details

https://www.academictransfer.com/328228/

Work Location(s)

Number of offers available

1

Company/Institute

Delft University of Technology

Country

Netherlands

City

Delft

Postal Code

2628 CD

Street

Mekelweg 2

Where to apply

Website

https://www.academictransfer.com/328228/phd-position-in-machine-learning-for-no…

Contact

City

Delft

Website

http://www.tudelft.nl/

Street

Mekelweg 2

Postal Code

2628 CD

STATUS: EXPIRED