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Scania Södertälje Heltid

30 hp – Neural Ordinary Differential Equations for Anomaly Detection

Detta jobb är inaktivt och går inte att söka längre.

About the job

Background

Scania is one of the world’s leading manufacturer of trucks and buses for heavy transports, as well as industrial and marine engines. Transport services and logistics services make up an increasing part of our business, which guarantees Scania’s customers cost-efficient transport solutions and high availability. Over a million Scania vehicles are in active use, in over 100 countries.

In the Connectivity section within Scania R&D, we develop new solutions for connected vehicles in our Internet of Things (IoT) platform, as part of Scania’s increasing focus on communication, services and smart transport solutions. Advanced data analysis capabilities are a cornerstone enabler in this development. 

Target/scope

Scania is developing data-driven methods for anomaly and fault detection using on-board time-series sensor data. These models range from statistical models to deep neural networks (DNN). Recently, a new type of neural networks was introduced, Neural Ordinary Differential Equations (NODE). In this thesis project we aim to implement NODE models for anomaly detection and compare their performance against DNN.

The student will have access to the necessary data and hardware for a successful project.

Description of the assignment

  1. Run and evaluate existing DNN anomaly detection models
  2. Implement a NODE for multivariate time-series anomaly detection model
  3. Evaluation of the implemented NODE
  4. Comparison of the NODE model against previously evaluated DNN model

If times permits

  • Explore NODE models specific characteristics to improve performance and accuracy
  • Compare optimized NODE models to existing DNN and Stat. Models

Education/line/direction

Assign education, line or direction: Masters programs in Machine Learning, Data Science, Computer Science, Engineering Physics, Engineering Mathematics, Media Technology, Complex Adaptive Systems or similar

Number of students: 1-2

Start date for the Thesis project: Anytime during fall 2021 or spring 2022

Estimated timescale: 20 weeks

Contact person and supervisor

Juan Carlos Andresen, Data Scientist, 08-553 835 16, juan-carlos.andresen@scania.com

Katarina Prytz, group manager, 08-553 723 08, katarina.prytz@scania.com

Application

Your application should contain the following: CV, personal letter, and copies of grades.

Date of publication, as from – through

Until 2021-06-27. Applicants will be assessed on a continuous basis until the position is filled.

Om företaget

Scania is a world-leading provider of transport solutions, including trucks and buses for heavy transport applications combined with an extensive product-related service offering. Scania offers vehicle financing, insurance and rental services to enable our customers to focus on their core business. Scania is also a leading provider of industrial and marine engines. In 2019, we delivered 91,700 trucks, 7,800 buses as well as 10,200 industrial and marine engines to our customers. Net sales totalled to over SEK 152 billion, of which about 20 percent were services-related. Founded in 1891, Scania now operates in more than 100 countries and employs some 51,000 people. Research and development are concentrated in Sweden, with branches in Brazil and India. Production takes place in Europe, Latin America and Asia, with regional production centers in Africa, Asia and Eurasia. Scania is part of TRATON SE.

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