Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- SciLifeLab
- University of Lund
- Umeå University
- Linköping University
- Lunds universitet
- Chalmers University of Technology
- Nature Careers
- KTH Royal Institute of Technology
- Uppsala universitet
- Karolinska Institutet (KI)
- Lulea University of Technology
- Stockholms universitet
- Swedish University of Agricultural Sciences
- Umeå universitet
- Umeå universitet stipendiemodul
- Chalmers University of Techonology
- Fureho AB
- Jönköping University
- Linköpings universitet
- Linnaeus University
- Mälardalen University
- School of Business, Society and Engineering
- Sveriges lantbruksuniversitet
- University of Gothenburg
- 14 more »
- « less
-
Field
-
focus on image processing and restoration, to develop novel AI-based approaches to restore and denoise Transmission Electron Microscopy (TEM) images. This position is part of a cross-disciplinary research
-
application! At the intersection between AI and single atoms. Your work assignments We are looking for a PhD student with a background in machine and deep learning with focus on image processing and restoration
-
, Experience in image processing and image analysis of tomographic or other imaging data, High motivation, ability to quickly learn new techniques, and strong time management skills, Strong collaboration and
-
using Cell Painting and high-content imaging. Deep learning and multivariate methods, both supervised and unsupervised. Development of software and pipelines for analysis of large-scale image data
-
in the acquired autoimmune disorder immune thrombocytopenia as well as in inborn errors of immunity. You will conduct research using human blood samples, processing them for imaging flow cytometry
-
across nine universities. CIPA is Lund University’s local infrastructure for image processing and analysis. CIPA is also the coordinating unit for Lund University's InfraVis node, consisting of around 10
-
. Your mission Understanding disease requires weaving together many layers of biological and clinical information. By fusing multimodal data including genomics, imaging, spatial omics, and patient records
-
to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for Data-Driven
-
on processing and analyzing large sets of medical brain imaging data. We have amassed large quantities of structural MRI (used to measure brain structure), diffusion MRI (used to measure brain connectivity) and
-
fluid dynamics and vascular modeling in microenvironments Skills in data analysis and image processing (e.g., Python, R, ImageJ) Ability to mentor junior researchers and contribute to team leadership What