Sort by
Refine Your Search
-
Listed
-
Employer
- Chalmers University of Technology
- Lunds universitet
- Karolinska Institutet (KI)
- Umeå University
- Linköping University
- SciLifeLab
- Umeå universitet stipendiemodul
- University of Lund
- KTH Royal Institute of Technology
- Nature Careers
- Uppsala universitet
- IFM/Linköping University
- KTH
- Karlstad University
- SLU
- Sveriges Lantbruksuniversitet
- 6 more »
- « less
-
Field
-
Intervention invites applications for a two‑year postdoctoral fellowship within the project AI‑Driven Medical Imaging. The position is expected to start on 1 September 2026 or as agreed. The fellowship is funded
-
, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses
-
of formulating them, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment
-
spectrometry. The project involves developing characterization methods using mass spectrometry (FT-ICR, TOF-SIMS) and imaging techniques (SEM, TEM) for both biological and inorganic materials. Responsibilities
-
Job Id: 11662 Limited to 2 years (with possibility of extension) | Full-time with 38,5 h | Salary according to TV-L E13 | European Institute for Molecular Imaging We are UKM. We have a clear social
-
Natural History. The researcher will develop deep learning models to predict individual bee age based on wing morphology. This model will be trained of existing wing images and applied to images of museum
-
strategies. The research group focuses on exploration of tumor immune microenvironments through spatial omics and imaging, development of computational models for prediction of molecular and clinical features
-
imaging, computer vision, and predictive modelling. The postdoc will further develop an existing rumen‑fill scoring algorithm into a functional prototype and pilot the technology for longitudinal monitoring
-
Description of workplace Diangostic Radiology, ITM, Lund University conducts research related to medical imaging diagnostics. LUCI (Lund University breast Cancer Imaging) is a cross-disciplinary
-
aggression, fear, and feeding), using large-scale neural recordings, advanced imaging, causal perturbations, and quantitative analysis in freely moving mice. For an overview of the lab’s research program and