Sort by
Refine Your Search
-
Category
-
Program
-
Field
-
of pancreatic cancer. This group is led by Associate Senior Lecturer Dr. Qiaoli Wang, as part of the SciLifeLab & Wallenberg National Program for Data-Driven Life Science (DDLS). Group members will be enrolled
-
, the University of Melbourne, and the University of California, Los Angeles. We strive for all PhD students to get a solid international experience during their PhD. About the DDLS Fellows program The PhD position
-
of biochemistry and biophysics, at Stockholm university. For more information about us, please visit: www.dbb.su.se . Main responsibilities The SciLifeLab and Wallenberg National Program for Data-Driven Life
-
studies. About the DDLS program Data-driven life science (DDLS) combines data, computational methods, and artificial intelligence to study biological systems from molecular structures to human health and
-
part of the SciLifeLab and the research school of the Wallenberg National Program for Data-Driven Life Science (DDLS), within the research area Cell and Molecular Biology. To achieve this, the doctoral
-
and biophysics, at Stockholm university. For more information about us, please visit: www.dbb.su.se . Main responsibilities At the SciLifeLab and Wallenberg National Program for Data-Driven Life Science
-
research and attractive study programmes attract researchers and students from around the world. With new knowledge and new perspectives, the University contributes to a better future. The Institute
-
devote oneself to a research project under supervision of experienced researchers and following an individual study plan. A doctoral degree corresponds to four years of full-time study. This is an industry
-
the BioImage Informatics team (https://www.scilifelab.se/units/bioimage-informatics/ ). This employment is funded through NBIS under the SciLifeLab and Wallenberg National Program for Data-Driven Life Science
-
requirements, please see the subject’s general study plan . The specific requirements are met by having passed exams in areas relevant to the subjects of image analysis and machine learning with a minimum of 90