Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Linköping University
- Uppsala universitet
- University of Lund
- Lunds universitet
- Swedish University of Agricultural Sciences
- Lulea University of Technology
- Umeå University
- University of Borås
- Chalmers University of Technology
- Luleå University of Technology
- Mid Sweden University
- SciLifeLab
- Stockholm University
- Stockholms universitet
- 4 more »
- « less
-
Field
-
‑mining and machine‑learning methods. The expected scientific outcome is to establish guidelines for identifying and optimizing promising electrolyte materials and to support the development of future
-
. The Regenerative Immunology lab is currently composed of three PhD students, three postdoctoral fellows, one MS student, and one animal technician. The lab resides within the Division of Molecular Medicine and Gene
-
. The PhD student will develop and apply analytical workflows to characterize complex food matrices. The project includes i) developing and optimizing screening workflows; ii) improving sample preparation
-
focuses on leveraging zebrafish as a model organism to develop and optimize genetic tools through a directed evolution pipeline, with significant therapeutic and industrial applications. Key
-
relevant not only for the organizations developing, training, or optimizing AI models, but in particular for users of the software products that inform and impact the policies that will regulate the AI
-
teaching in key and rapidly evolving areas such as autonomous systems, data-driven modeling, learning-based control, optimization, complex networks, and sensor fusion. Research at the division is
-
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
-
existing and creating new deep learning-based models for anomaly detection, theoretical and numerical studies of detection quality, creating new distributed computational pipelines and optimizing
-
algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics, spanning diverse application domains such as medicine, energy systems, biomedical
-
, spectroscopic signatures, microstructural images, processing conditions, and macroscale performance will be used for the optimization of materials. The candidate will collaborate extensively with in