Scania genomgår nu en transformation från att vara en leverantör av lastbilar, bussar och motorer till en leverantör av kompletta och hållbara transportlösningar.
At the department of
Autonomous Transport Systems (ATS)
, we develop a full stack prototype system for sustainable autonomous driving. The work is done in close cooperation with Volkswagen group, leading technology suppliers and academic institutions. We take responsibility for creating a better and greener environment by finding answers to the questions on how we can achieve radically reduced emissions, manage the negative effects of ongoing urbanisation and save human lives in traffic.
A master thesis project in the AI Technologies group at ATS research, is a great opportunity to work on the forefront of autonomous vehicle development and machine learning technologies, that help to enable automated driving in complex driving environments. Many of our current employees have started their careers with a thesis project. We also have plenty of opportunities for both PhD and expat positions.
The AI Technologies group is responsible for the development of Artificial Intelligence based functions for our autonomous driving pipeline. Most of our work currently circle around computer vision and deep learning, but we have plenty of ground to cover also outside of these domains.
Below are two topics we are interested in exploring within the AI Technologies group. In both proposals you will as part of the thesis develop neural networks using our deep learning development infrastructure based on TensorFlow and Keras. Our pipeline is prepared for testing the final algorithms on the target system in our prototype self-driving vehicle, this is the goal for all our work including thesis projects. Depending on the successful applicant’s background, strengths and interests, we are flexible in the exact definition of the thesis.
Thesis 1: Object Separation using Semantic Segmentation and Bounding Boxes for Image Data
key performance indicators
Thesis 2: Real-Time Uncertainty Estimation for Semantic Segmentation Neural Networks.
Monte Carlo Dropout
key performance indicators
Education and skills
Master student (Civilingenjör) in computer science, mathematics, physics or similar, preferably with specialization in computer vision, machine learning, artificial intelligence, data science, and robotics.
Documented experience and skills in Python and C++, in addition to machine- and deep learning, is a merit.
The work will be carried out at our offices in Södertälje. A thesis project is a great way to learn more about Scania and our many interesting career opportunities.
Number of students: one student per topic (two in total)
Start date: Autumn 2019 or Spring 2020
Estimated time needed: 20 weeks, Full-time Language of work: Good knowledge in English is required
Contact persons and supervisors
Mikael Johansson, AI Team Leader, 08 553 533 45
Addi Djikic, Supervisor, 08 553 722 68
Ezeddin Al Hakim, Supervisor, 08 553 534 91
Enclose CV, personal letter (also mentioning the preferred thesis) and grades.