Tag-arkiv: Mälardalen University

PhD student in Computer Science – Modeling and development of distributed embedded systems based on TSN-5G networks

Ref.nr: 2020/0860

The research environment Embedded Systems (ES) at Mälardalen University (MDH) announces a PhD-student position in Computer Science. ES is the nationally leading center in embedded-systems research and internationally known for the ability to combine the highest academic standard with industrially relevant research. ES provides a stimulating international research environment, characterized by its cooperative atmosphere, openness, and team spirit – a great environment for a researcher to grow in; with a mix of established and young researchers. The environment contains over 200 researchers.

Employment information

Employment: Temporary employment
Scope: Full time
Closing date for application: 2020-04-30
Campus location: Västeras
School: School of Innovation, Design and Engineering, (IDT)

Position description

The VINNOVA-funded project “PROVIDENT: Predictable Software Development in Connected Vehicles Utilising Blended TSN-5G Networks” is announcing a PhD position in modeling and development of distributed embedded systems based on TSN-5G networks.

Modern vehicles in many segments of the vehicular domain need to communicate and collaborate to achieve a joint functionality in, e.g., an autonomous quarry, mine or a recycling site. To provide such functionality, these vehicles need to be equipped with high data-rate sensors (e.g., cameras and lidars). The large amount of data acquired from these sensors needs to be communicated within as well as among the vehicles with predictable low latencies. The recently introduced IEEE Time-Sensitive Networking (TSN) standards and 5G communication offer promising solutions to address these requirements within and among the vehicles respectively. Alas, there is a lack of a holistic software development framework and execution environment for predictable vehicular systems that utilise blended TSN-5G communication. This lack hinders the vehicle industry from taking full advantage of these ground- breaking technologies.

The overall goal of PROVIDENT is to develop novel techniques to provide a full- fledged holistic software development environment for vehicular systems that utilise blended TSN- 5G communication. In this context, the PhD-student will focus on the challenges related to holistic modelling of software architectures, holistic timing predictability verification, and integration of network communication in vehicular systems that utilise a blend of TSN-5G networks. The student will work closely with the project team of about 15 members, including researchers from Mälardalen University and practitioners from the industrial partners. The student is also expected to work indepefndently.


Only those who are or have been admitted to third-cycle courses and study programmes at a higher education may be appointed to doctoral studentships. For futher information see Chapter 5 of the Higher Education Ordinance (SFS 1993:100).

To qualify as a PhD student, you should have a master’s level degree in computer science, computer engineering, electrical engineering, or equivalent. Prior knowledge about embedded systems, real-time systems, real-time networks, and modeling and timing analysis of these systems is considered a merit. Additional knowledge in applied mathematics, model-based software development and development of switched Ethernet-based systems is also considered as merit.

The position requires a strong motivation for research, good verbal and written communication skills in English. Decisive importance is attached to personal suitability. We value the qualities that an even distribution of age and gender, as well as ethnic and cultural diversity, can contribute to the organization.


Application is made online. Make your application by clicking the “Apply” button below.

The applicant is responsible for ensuring that the application is complete in accordance with the advertisement and will reach the University no later than closing date for application.

We look forward to receiving your application.

We decline all contact with recruiters and salespersons of advertisements. We have made our strategic choices for this recruitment.


Saad Munbeen

Associate Prof


Mohammad Ashjaei

Assistant Prof


Michaël Le Duc

Union SACO

021-10 14 02

Susanne Meijer

Union (OFR)

021-10 14 89

Read the job description at the university homepage


Post expires on Thursday April 30th, 2020