Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
technology Researcher Profile First Stage Researcher (R1) Application Deadline 14 May 2026 - 21:59 (UTC) Country Sweden Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research
-
Rising Innovative city . The position is formally based at the Division of Statistics and Machine Learning (STIMA) within the Department of Computer and Information Science. At STIMA we conduct research
-
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
-
, administrative and technical support functions, along with good employment conditions. More information about the department is available at: https://www.umu.se/en/department-of-computing-science/ . Project
-
and technical support functions, along with good employment conditions. More information about the department is available at: https://www.umu.se/en/department-of-computing-science/ . Project
-
distributed computational pipelines and optimizing communication costs. You will also contribute to the integration and testing of the models in real D-MIMO environments, in close collaboration with a PhD
-
, and datasets; often at substantial computational and environmental costs. This PhD project targets sustainable and resource-efficient machine learning with a focus on methods that reduce compute, energy
-
workplace You will be employed in either the Division of Cyber Security (CYBER) or the Division of Artificial Intelligence and Integrated Computer Systems (AIICS) at the Department of Computer and Information
-
at the Division of Statistics and Machine Learning (STIMA) at the department of computer and information science . At STIMA, we conduct research and education in both statistics and machine learning
-
, where AI models are trained without having all data in a single computer. This makes it possible to use larger datasets for training, without sending sensitive data between hospitals. The goal is to