CARIAD SE
Internship / Masters Thesis - Sim-to-Real Transfer in Reinforcement Learning(m/w/x)
Full-timeInternshipWith Homeoffice
from 13.9 / hour
Mönsheim, München, Berlin
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CARIAD SEInternship / Masters Thesis - Sim‑to‑Real Transfer in Reinforcement Learning(m/w/x)
Mönsheim, Berlin, München
from 13.9 / hour
Full-timeInternshipWith Home Office
Description
You will bridge the gap between simulation and reality by developing robust reinforcement learning policies, collaborating with researchers to transform automotive mobility through advanced AI.
Let AI find the perfect jobs for you!
Upload your CV and Nejo AI will find matching job offers for you.
Requirements
- •Enrolled student in relevant technical field
- •Foundation in machine and reinforcement learning
- •Solid Python and ML framework skills
- •Experience with learning-based simulation models
- •Basic understanding of control systems (plus)
- •Structured, independent working style and analytical skills
- •Fluency in English and German
Education
Currently in higher education
Tasks
- •Partner with a PhD student on reinforcement learning
- •Review state-of-the-art domain randomization and policy transfer
- •Investigate advanced techniques to improve policy robustness
- •Use measurement data to reduce simulation-to-reality gaps
- •Design experiments to evaluate randomization and adaptation strategies
- •Implement prototype learning pipelines and validate methods
- •Collaborate with pre-development and series development teams
Tools & Technologies
PythonJAX
Languages
English – Business Fluent
German – Business Fluent
Benefits
Other Benefits
- •Application assistance for disability
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of CARIAD SE and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
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CARIAD SEInternship / Masters Thesis - Sim‑to‑Real Transfer in Reinforcement Learning(m/w/x)
Mönsheim, Berlin, München
from 13.9 / hour
Full-timeInternshipWith Home Office
New Job?Nejo!
The AI Job Search Engine
Description
You will bridge the gap between simulation and reality by developing robust reinforcement learning policies, collaborating with researchers to transform automotive mobility through advanced AI.
Let AI find the perfect jobs for you!
Upload your CV and Nejo AI will find matching job offers for you.
Requirements
- •Enrolled student in relevant technical field
- •Foundation in machine and reinforcement learning
- •Solid Python and ML framework skills
- •Experience with learning-based simulation models
- •Basic understanding of control systems (plus)
- •Structured, independent working style and analytical skills
- •Fluency in English and German
Education
Currently in higher education
Tasks
- •Partner with a PhD student on reinforcement learning
- •Review state-of-the-art domain randomization and policy transfer
- •Investigate advanced techniques to improve policy robustness
- •Use measurement data to reduce simulation-to-reality gaps
- •Design experiments to evaluate randomization and adaptation strategies
- •Implement prototype learning pipelines and validate methods
- •Collaborate with pre-development and series development teams
Tools & Technologies
PythonJAX
Languages
English – Business Fluent
German – Business Fluent
Benefits
Other Benefits
- •Application assistance for disability
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of CARIAD SE and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
About the Company
CARIAD SE
Industry
Automotive
Description
The company builds automotive software platforms and digital customer functions for brands like Audi, Volkswagen, and Porsche.
Not a perfect match?
- CARIAD SE
Internship / Masters Thesis - Sim-to-Real Transfer in Reinforcement Learning(m/w/x)
Full-timeInternshipWith Homeofficefrom 13.9 / hourMönsheim, München, Berlin - CARIAD SE
Internship / Masters Thesis - Meta-Reinforcement Learning for Vehicle Functions(m/w/x)
Full-timeInternshipWith Homeofficefrom 13.9 / hourMönsheim, München, Berlin - CARIAD SE
Internship / Masters Thesis - Inverse Reinforcement Learning for Vehicle Functions(m/w/x)
Full-timeInternshipWith Homeofficefrom 13.9 / hourMönsheim, München, Berlin - CARIAD SE
Internship / Thesis - System Identification with Physics-informed ML for Vehicle Dynamics(m/w/x)
Full-timeInternshipWith Homeofficefrom 13.9 / hourBerlin, München, Mönsheim - Bosch Group
Master Thesis Neural Network-Based Surrogate Models for EHL Contact Simulations(m/w/x)
Full-timeInternshipWith HomeofficeRenningen