Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
, Chemistry and Biology (IFM), Linköping University. You will be part of the Laboratory of Molecular Materials (m2lab), an interdisciplinary research environment focusing on bioresponsive materials and devices
-
look forward to receiving your application! If you have experience in research on canine behavioural biology and are skilled at analysing large datasets, this position may be the right fit for you! Work
-
participation in regular group meetings and events. You can read about the workplace: https://liu.se/en/organisation/liu/ifm/mdesign The employment This employment is a temporary contract of two years with
-
successful candidate should have excellent study results and a strong background in mathematics. The applicant should be skilled at implementing new models and algorithms in a suitable software environment
-
performance should improve over time as more data becomes available. The diagnostic conclusions will be presented to an operator using a combination of AI-based fault isolation algorithms and data-driven
-
artificial intelligence and control systems. In this project, you will design new algorithms for semantic communication between the cloud and autonomous systems—technology that can transform how robots, drones
-
distributed wireless systems" which is conducted in collaboration between Linköping University (LiU) and Lund University (LU). Read more here: https://elliit.se/project/machine-learning-for-sensing-in
-
usage, memory and storage demands, and associated carbon emissions while aiming to maintain model quality. Your work will include developing new methodologies and algorithms for resource-efficient
-
precision medicine based on gene sequencing time series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related
-
algorithms for resource-efficient learning, for example via data selection and filtering (leveraging that not all data is equally informative). You will also investigate complementary approaches that reduce