Sort by
Refine Your Search
-
application! We are now looking for a PhD student in Computer Vision and Learning Systems at the Department of Electrical Engineering (ISY). Your work assignments Your task will be to analyse and adapt vision
-
application! We are seeking a highly motivated PhD student to join a research project at the forefront of battery diagnostics and modelling, that will help shape the future of battery technology by developing
-
University is currently conducting a highly relevant research project focusing on issues related to sustainability and total cost. We are now seeking a PhD candidate for this project. We are looking
-
, and vehicles collaborate. Your work assignments You will work in the ELLIIT funded project “Safety-Critical Intelligent Machines with Cloud-Assisted AI and Control”. This project focuses on safety
-
satellite‑based techniques to help accelerate a sustainable climate transition in the agricultural sector. As a PhD student you will be part of a competent, open, and welcoming research group at Linköping
-
well as the efficacy of the live rotavirus vaccines. In this project we will combine evolutionary analyses, historical data, and functional organoid studies in a multidisciplinary approach. By performing analysis
-
innovative materials design are essential for a sustainable society. In the Green Polymer Chemistry (GreenPolChem) group comprised of 10 researchers, located in the Pronova Chemistry Lab at the Laboratory
-
this field and currently includes around 50 PhD students and 20 postdoctoral researchers. Green chemistry, bio-based building blocks, and innovative materials design are essential for a sustainable society. In
-
vehicles). As a PhD student, you devote most of your time to doctoral studies and the research projects of which you are part. Your work may also include teaching or other departmental duties, up to a
-
distributed MIMO systems. Your work assignments The research focus for the advertised position is machine learning for telecommunications. The position is part of the project "Machine learning for sensing in