Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- SciLifeLab
- Umeå University
- Lunds universitet
- KTH Royal Institute of Technology
- Chalmers University of Technology
- Karolinska Institutet (KI)
- University of Lund
- Uppsala universitet
- Linköping University
- Chalmers tekniska högskola
- Nature Careers
- Swedish University of Agricultural Sciences
- Umeå universitet
- Umeå universitet stipendiemodul
- Högskolan Väst
- Stockholms universitet
- University of Gothenburg
- Chalmers University of Techonology
- Fureho AB
- Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg
- Jönköping University
- Karolinska Institutet, doctoral positions
- Linköpings University
- Linköpings universitet
- Linnaeus University
- Linneuniversitetet
- Lulea University of Technology
- Luleå University of Technology
- Luleå tekniska universitet
- Lund University
- Mälardalen University
- SLU
- School of Business, Society and Engineering
- Sveriges Lantbruksuniversitet
- Sveriges lantbruksuniversitet
- 25 more »
- « less
-
Field
-
master degree degree is required in relevant areas such as remote sensing, computer sciences, and mathematics. You are also required to have strong background in deep learning for image analysis, e.g
-
Protein Expertise Platform, X-ray, proteomics, NMR (850-400 MHz), cryo-EM and Biochemical Imaging Centre (confocal, SIM, FLIM, spinning disk, TIRF, STORM). Project description Autophagy is an evolutionarily
-
tissue using spatial transcriptomics, electrophysiology, imaging-based assays, and integrative data analysis. The goal is to map disease-related cellular states and spatial patterns of dysfunction in
-
or white light interferometry Microscopy and image analysis (e.g., SEM, fluorescence microscopy) Antimicrobial testing or microbiology techniques Cell biology and molecular biology techniques (e.g., qPCR
-
defects, using both patient samples and model systems (mouse and fly). Implement methods for advanced image analysis. Develop strategies for metabolic tracing in tissues. You will collaborate closely with
-
for multimodal machine learning, combining large-scale image data with molecular profiling and clinical data. This includes, for instance, research on deep learning-based image analysis and data assimilation
-
with characterization techniques (such as optical & scanning electron microscopy, image analysis, microhardness measurement etc.) Some of the experiments are expected to be conducted in close
-
dynamics and heat transfer research. Programming skills in Python and MATLAB, particularly in machine learning, data analysis, and image processing. Experience working in Linux environments. Ability
-
world-leading research environment through the development of paradigm-shifting knowledge about bio-based wood adhesives in three research areas: raw materials and formulations, aspects of adhesives, as
-
: The position demands a technical background in and skills related to: Detailed characterization of materials (morphology and microstructure by optical & scanning electron microscopy, image analysis