31 data "https:" "https:" "https:" "https:" "UCL" "Brunel University London" PhD positions at Linköping University
Sort by
Refine Your Search
-
-assisted AI and control systems is to deliver the right and significant piece of information to the right point of computation (or actuation) at the correct moment in time. To address this challenge, you
-
17 Mar 2026 Job Information Organisation/Company Linköping University Research Field Computer science Researcher Profile First Stage Researcher (R1) Application Deadline 13 Apr 2026 - 12:00 (UTC
-
/tensions between the global North and global South. We will also consider applicants focused primarily on Swedish/Nordic cases or topics. For full information of the five REMESO research streams see: https
-
of machine learning which clearly integrates the two subject areas within the division. For more information about STIMA, please see https://liu.se/organisation/liu/ida/stima . Linköping University is
-
of Computer and Information Science , within Linköping University . Your work assignments As a PhD student, you devote most of your time to doctoral studies and the research projects of which you are part. Your
-
conducted in collaboration between Linköping University (LiU) and Lund University (LU). Read more here: https://elliit.se/project/machine-learning-for-sensing-in-distributed-wireless-systems/ Distributed MIMO
-
competitive advantage (https://liu.se/en/research/cbmi ). You will work under the supervision of Professors Christian Kowalkowski and Daniel Kindström. Research at IEI spans a broad range of areas, from
-
research at LiU: https://liu.se/en/research/cybersecurity The employment When taking up the post, you will be admitted to the program for doctoral studies. More information about the doctoral studies at each
-
solutions across the natural sciences. Your workplace You will be employed at the Department of Mathematics in the Division of Applied Mathematics, https://liu.se/en/organisation/liu/mai/tima . The research
-
learning, for example via data selection and filtering (leveraging that not all data is equally informative). You will also investigate complementary approaches that reduce inference and deployment costs