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Postdoc Reinforcement Learning and Control: An Algorithmic Approach

The Human Resources Strategy for Researchers
15 Mar 2024

Job Information

Organisation/Company
Delft University of Technology (TU Delft)
Research Field
Technology
Researcher Profile
First Stage Researcher (R1)
Country
Netherlands
Application Deadline
Type of Contract
Temporary
Job Status
Not Applicable
Hours Per Week
40.0
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

Recent developments in sensing and communication technology offer unprecedented opportunities by ubiquitously collecting data at high detail and at large scale. Utilization of data at these scales, however, poses a major challenge for control systems, particularly in view of the additional inherent uncertainty that data-driven control signals introduce to systems behavior. In fact, this effect has not been well understood to this date, primarily due to the missing link between data analytics techniques in machine learning and the underlying physics of dynamical systems.

The goal of this project is to address this issue by proposing a novel control design paradigm embracing ideas from the emerging field of distributionally robust optimization (DRO). DRO is a decision-making model whose solutions are optimized against all distributions consistent with given prior information. Recent breakthrough work, among others by the PI of this proposal, has shown that many DRO models can be solved in polynomial time even when the corresponding stochastic models are intractable. DRO models also offer a more realistic account of uncertainty and mitigate the infamous post-decision disappointment of stochastic models.

Requirements

Specific Requirements

Candidates for this challenging project should have a PhD degree and background in e.g., systems and control, computer science, applied mathematics, electrical engineering, mechanical engineering, or chemical engineering. The candidate must be enthusiastic and greatly interested in fundamental research in addition to having good programming skills for implementing state-of-the-art advanced algorithms. Familiarity or previous experience with the following topics is a plus: model predictive control, model-based and data-driven fault detection and identification, moving horizon estimation, convex optimization, randomized algorithms, stochastic programming, machine learning. In addition, excellent communication skills are important for this position and a good command of the English language is required. Previous experience in an industrial environment or serving as a liaison with industrial partners is a plus. We offer the opportunity to perform scientifically challenging research in a multi-disciplinary research group in collaboration with several key industrial partners in high-tech manufacturing.

Additional Information

Benefits

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities (salary indication: € 4.036 - € 5.090 per month gross). The TU Delft offers a customisable compensation package, discounts on health insurance, 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.

The appointment will be for 1 year, with the possibility for extension up to 3 years.

Selection process

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

Additional comments

For more information about this vacancy, please contact Peyman Mohajerin Esfahani, p.mohajerinesfahani@tudelft.nl.

Are you interested in this vacancy? Please apply by 31 March 2024 via the application button and upload:

  • motivation letter
  • detailed CV
  • names and contact information of 3 references.

For information about the application procedure, please contact Linda Ruijters, HR Advisor, recruitment-me@tudelft.nl.

Notes:
- You can apply online. We will not process applications sent by email and/or post.
- Please do not contact us for unsolicited services.

Website for additional job details

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
Geofield

Contact

City
Delft
Website
Street
Mekelweg 2
Postal Code
2628 CD