Webbjobb.io använder cookies för att hjälpa oss göra webbplatsen bättre. Genom att surfa vidare godkänner du lagringen av dessa. Läs mer om cookies.
Webbjobb.io använder cookies för att hjälpa oss göra webbplatsen bättre. Genom att surfa vidare godkänner du lagringen av dessa. Läs mer om cookies.
- Notera att ansökningsdagen för den här annonsen kan ha passerat. Läs annonsen noggrant innan du går vidare med din ansökan.
Background
Recent growth in the research activities and the well-established educational programs of the School of Information Technology (ITE) is enabling a significant expansion.
In 2018 the total research expenditures exceeded 70 MSEK and the school hosted over 850 students. Over the next two years, the School will grow significantly.
ISDD is carrying out several application-oriented research projects together with various companies in the data mining/machine learning area. The position is funded by the HEALTH (“Hazard Estimation and Analysis of Lifelong Truck Histories”) and EVE ("Extending life of Vehicles within Electromobility era") project. The general objective of this position is to build machine learning models for predicting heavy duty vehicle’s component failure, including unit injector, alternator, air compressor and air dryer etc., based on vehicle sensor data.
Work tasks include
- Preprocessing of vehicle sensor readings
- Applying machine learning algorithm to cast prediction on health status of vehicle components
- Valuating the approach and analyse the feasibility of deployment.
Qualifications
- Licentiate degree or higher
- Experiences in working with predictive maintenance related projects for heavy duty vehicles
- Proficient in Python, SPSS and SQL database.
Salary
Salary is to be determined by negotiation.
Application
Applications should be done via Halmstad University's recruitment system Varbi (see link on this page). The application shall consist of:
1) a personal letter stating why you believe that your goals and experiences are well-matched with the goals of this position.
2) CV
General Information:
We value the qualities that gender balance and diversity bring to our organisation. We therefore welcome applicants with different backgrounds, gender, functionality and life experience.