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Master thesis - Efficient World Representations for End-to-End Autonomous Driving

Technology, Data & Digital · Data, AI & Analytics · Machine Learning · Artificial Intelligence · Software Engineering

In short

This Master's thesis focuses on developing efficient world representations for end-to-end autonomous driving at TRATON Group R&D. You will investigate compact, task-aligned representations of sensor data for real-time trajectory planning in heavy-duty vehicles using public datasets and open-source models.

Responsibilities

  • Review relevant literature and help define a focused research question.
  • Set up or reproduce an open-source autonomous-driving model, simulator, or benchmark.
  • Implement and evaluate a method, benchmark extension, or experimental framework.
  • Analyze relevant trade-offs in planning performance, safety, generalization, latency, memory, or computational cost.
  • Document the work, present the results, and write the final thesis report.

Requirements

  • Pursuing a Master's degree in computer science, machine learning, robotics, engineering physics, electrical engineering, or a related technical field.
  • Strong programming skills, preferably in Python and PyTorch.
  • Knowledge of machine learning and deep learning.
  • Interest in autonomous driving, computer vision, transformers, representation learning, or simulation.
  • Motivation to combine scientific investigation with practical implementation.

Desired Qualifications

  • Experience with articulated or configuration-dependent constraints in autonomous driving.
  • Familiarity with evaluation and extension of public benchmarks.

Benefits

  • Contribute to EGoPT, a new industrial research project on World Models for Autonomous Driving.
  • Build relationships for the future within TRATON Group R&D.
  • Gain practical experience with state-of-the-art autonomous driving technology.

Skills

PythonPyTorchMachine LearningDeep LearningComputer VisionTransformersRepresentation LearningSimulation
#autonomous driving#world models#machine learning#deep learning#robotics#computer vision#representation learning#simulation#thesis#master's thesis
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About Scania Group

Scania is a world-leading provider of transport solutions committed to a better tomorrow. Our purpose is to drive the shift towards a sustainable transport system. In doing so, we are creating a world of mobility that’s better for business, society and our environment. Employing more than 50,000 people in about 100 countries, Scania’s research and development is concentrated in Sweden, while production takes place in Europe and South America.

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Company

Scania Group

Job Posted

2 days ago

Employment Type

Full Time

Work mode

Hybrid

Experience Level

Entry

Locations

Södertälje, Sweden

Qualification

Master

Applicants

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