Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- KTH Royal Institute of Technology
- SciLifeLab
- Sveriges lantbruksuniversitet
- Chalmers University of Technology
- Linköping University
- Umeå University
- Lunds universitet
- University of Gothenburg
- Luleå University of Technology
- Karolinska Institutet (KI)
- Lulea University of Technology
- Chalmers tekniska högskola
- Nature Careers
- Blekinge Institute of Technology
- University of Lund
- Örebro University
- Uppsala universitet
- Linnaeus University
- Umeå universitet stipendiemodul
- Högskolan Väst
- Jönköping University
- Stockholms universitet
- Umeå universitet
- Chalmers Tekniska Högskola AB
- Chalmers University of Techonology
- Epishine
- Fureho AB
- Karolinska Institutet, doctoral positions
- Linköpings universitet
- Linneuniversitetet
- Lund university
- Malmö universitet
- Mälardalen University
- School of Business, Society and Engineering
- Swedish University of Agricultural Sciences
- Södertörn University
- 26 more »
- « less
-
Field
-
their ability to: independently pursue his or her work collaborate with others, have a professional approach and analyze and work with complex issues. Experience in machine learning, algorithmic theory, or code
-
information about us, please visit: www.dbb.su.se . Main responsibilities SciLifeLabs Cell and Molecular Imaging (CMI) platform offers access to advanced imaging technologies, from cryo-EM and tomography
-
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
-
dynamics to cellular metabolism. The student will receive broad training in cell culture, genome engineering, live-cell imaging, biochemical assays, proteomics, and computational data analysis, and will work
-
, BCI), physiological data, and medical image/microscopy analysis. Excellence in foundational and applied research, demonstrated by publications in leading AI/ML and medical imaging venues (e.g., MICCAI
-
Cancer is a leading cause of death globally, and analyzing digital pathology images for cancer diagnosis and treatment is a complex problem due to the high data volume, variability, and computational
-
and survival in host cells. Through a combination of microbiology, imaging, molecular biology, and translational modelling, the PhD student will generate data to support the design of biofilm-resistant
-
Proteomics unit you will be responsible for data management and infrastructure, implementation and development of analysis pipelines. You will work on different datasets and help our users with image and
-
Electron Microscopy (TEM) and HAADF-STEM images. Microscopy data are often degraded by noise and scan distortions, and clean ground truth data are rarely available. This project aims to go beyond standard
-
the development of hyperspectral 3D electric field imaging techniques in the THz spectral range, utilizing ultrashort lasers and nonlinear optical methods. The work will be conducted at KTH Laser Lab research