Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Karolinska Institutet
- Karolinska Institutet (KI)
- Chalmers University of Technology
- Lunds universitet
- Uppsala University
- SciLifeLab
- Uppsala universitet
- Linköping University
- Umeå University
- Nature Careers
- Örebro University
- Karolinska Institute
- SLU (Swedish University of Agricultural Sciences)
- Sveriges lantbruksuniversitet
- Swedish University of Agricultural Sciences
- 5 more »
- « less
-
Field
-
), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. Your work will be in at the department for medical radiation physics, in the experimental x-ray group headed by
-
of the results. To achieve this, you will need, among other things, expertise in advanced statistical methods and handling of complex and extensive datasets. The work includes data from medical records and the
-
The Department of Medical Biosciences is seeking a motivated and scientifically driven postdoctoral researcher in pathology for translational studies related to aggressive prostate cancer. The appointment aims
-
intervention and implementation research in the field of diet, physical activity, family support and obesity prevention for children between 6-12 years old. The project aims to link two evidence-based
-
Do you want to contribute to top quality medical research? We are seeking a postdoctoral fellow who will work on an exciting collaborative initiative aimed at investigating the impact of perinatal
-
» Biochemistry Physics » Biophysics Medical sciences » Other Researcher Profile Recognised Researcher (R2) Country Sweden Application Deadline 20 Apr 2024 - 21:59 (UTC) Type of Contract Other Job Status Full-time
-
Do you want to contribute to top quality medical research? The successful candidate will work on childhood neuroblastoma and paraganglioma in the research group headed by Susanne Schlisio
-
cells. The models encompass metabolism, signaling, and gene regulation and are constrained to align with physical interactions between biomolecules. We train the models on high-throughput datasets
-
metabolism, signaling, and gene regulation and are constrained to align with physical interactions between biomolecules. We train the models on high-throughput datasets, including metabolomics, proteomics, and
-
cells. The models encompass metabolism, signaling, and gene regulation and are constrained to align with physical interactions between biomolecules. We train the models on high-throughput datasets