Doctoral student position in Electrical Engineering with focus on Machine Learning for IoT Systems at the Faculty of Engineering, Lund University.

Subject description

Machine learning and artificial intelligence have attracted a lot of attention over the past few decades. Machine learning algorithms have been considered in many application domains, including Internet of Things (IoT) systems. The adoption of machine learning in IoT systems creates several new opportunities, e.g., detection of health abnormalities using wearable devices, but also involves several major challenges, e.g., complexity of machine learning algorithms for IoT systems and privacy concerns related to personal data and machine learning.

Work duties

The Doctoral student will work within the area of machine learning for IoT systems to tackle one of the main challenges in the machine learning domain. The project is cross-disciplinary between the machine learning and IoT areas, e.g., edge machine learning on IoT devices. An important part of the student’s work will be to develop the theoretical foundation of machine learning and new algorithms to address the challenges within the subject area of this position. The student will also be given the opportunity to validate these solutions with experiments and simulations.

The main duties of doctoral students are to devote themselves to their research studies which includes participating in research projects and third cycle courses. The work duties will also include teaching and other departmental duties (no more than 20%).

More Information and Application

View all positions
We use cookies to personalise content and ads, to provide social media features and to analyse our traffic. We also share information about your use of our site with our social media, advertising and analytics partners. View more
Cookies settings
Accept
Privacy & Cookie policy
Privacy & Cookies policy
Cookie name Active
The WASP website wasp-sweden.org uses cookies. Cookies are small text files that are stored on a visitor’s computer and can be used to follow the visitor’s actions on the website. There are two types of cookie:
  • permanent cookies, which remain on a visitor’s computer for a certain, pre-determined duration,
  • session cookies, which are stored temporarily in the computer memory during the period under which a visitor views the website. Session cookies disappear when the visitor closes the web browser.
Permanent cookies are used to store any personal settings that are used. If you do not want cookies to be used, you can switch them off in the security settings of the web browser. It is also possible to set the security of the web browser such that the computer asks you each time a website wants to store a cookie on your computer. The web browser can also delete previously stored cookies: the help function for the web browser contains more information about this. The Swedish Post and Telecom Authority is the supervisory authority in this field. It provides further information about cookies on its website, www.pts.se.
Save settings
Cookies settings