Physics-guided learning for machine control Full-time

Offer Description

Robust machine control assumes modeling of robot-environment interactions. An example may include an outdoor autonomous ground robot that needs to be aware of its model and how the terrain will interact with it when a control sequence is executed. A flying robot may benefit from knowing the wind field ahead to model aerodynamic forces correctly.

However, building robust perception systems that can efficiently adapt in a self-supervised manner to novel environments remains a significant challenge. We identify three core issues: (i) black-box models that ignore the robot’s physical embodiment suffer from poor generalization, weak explainability, and limited transferability; (ii) sample-inefficient learning requires large volumes of annotated, domain-specific data; and (iii) complex architectures with tightly coupled components hinder modular adaptation. To address these limitations, we research a physics-guided machine learning framework that integrates physical knowledge with data-driven methods. Physical knowledge includes, among others, kinematics and the dynamics of the robot, terrain interaction and contact models, and environmental physics, such as wind. The physics can be incorporated in various ways. Two methods now researched most intensively are i) trainable machine learning pipelines may embed differentiable physical models, and ii) the learning process may be informed by constraining the predicted variable to obey physical laws; we can see it as physics-informed losses. We will seek new ways to embed the physics.

Our approach aims to enable explainable, embodiment-aware, and probabilistically consistent adaptation from onboard sensory data via end-to-end differentiable architectures, enhancing robustness, efficiency, and generalization across diverse robotic platforms and environments.

Where to apply
E-mail
[Please click the Apply button for the link or address]

Requirements

Research Field Computer science ” Informatics Education Level PhD or equivalent

Skills/Qualifications

E ducation, research experience and publication record in areas relevant to the research topic

Specific Requirements

Required documents to be uploaded to the Application form webpage

1. CV including a list of
   a) Invited presentations to conferences and/or international advanced schools,
   b) Organisation of International conferences (membership in the steering and/or programme committee),
   c) Prizes, Awards, and Scholarships
   d) Projects funded and/or active participation,
   e) Examples of participation in industrial innovation, if any.
2. List of publications
   Journal papers first, conference papers second, followed by patents.
3. Research proposal
   Select one of the topics offered
   Describe the scope, objectives and foreseen research and training activities, including cooperation with the Associated partner.
   Required sections: 1) Excellence, 2) Impact incl. expected outputs of the project, 3) Quality and Efficiency of the Implementation 4), Personal motivation: description of career goals, foreseen advancement in research and professional skills of the Applicant.
   Consult your proposal with the respective Mentor. You are encouraged to communicate with the mentor before you submit the application.
4. PhD diploma (or certificate of defense)

Languages ENGLISH Level Good

Additional Information

Benefits

Gross monthly salary of 83 531 CzK/month*
Family allowance 9044 CZK/month (for applicants with dependent family members)
Travel support for conferences and secondments
Research costs1

*The gross monthly salary CZK is under the standard scheme in the Czech Republic and includes mandatory social and health insurance. Therefore, the gross salary contains an employee contribution to social and health insurance of 11% and it is standardly taxable (15 % rate). Some tax discounts are given to e.g. employees with children.

Example: a single researcher would get 61 813 CzK as net salary

The offered salary is equivalent to the standard MSCA individual postdoc award, and it is highly competitive (double the average salary in Czechia, the typical salary of an Associate professor)

Eligibility criteria

Experience :
* PhD degree at the time of beginning of the contract
Applicants who are close to the defense of their doctoral thesis will also be considered eligible to apply

* maximum of 8 years experience in research , from the date of the award of their PhD degree till the time of the Call opening (July 26, 2025) . Years of experience outside research and career breaks will not count towards the above maximum.

* previous studies compatible with the project they intend to apply with

Mobility : applicants must not have resided or carried out their main activity in the Czech Republic for more than 12 months in the 3 years prior to the Calls’ deadline (career breaks not counted).

Selection process

2-stage

Applicants should select one topic from the List of topics and prepare their own Research proposal.
It is recommended that the applicants contact the Mentor of the relevant topic and consult their proposal in advance.

The Application form is open for modifications until the deadline.

Website for additional job details

https://cyber.fel.cvut.cz/

Work Location(s)

Number of offers available 1 Company/Institute Department of Cybernetics Country Czech Republic City Prague 2 Postal Code 120 00 Street Karlovo náměstí 13 Geofield

Tagged as: Physics