Sort by
Refine Your Search
-
and experiences. We regard gender equality and diversity as a strength and an asset. The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) is a 12-yr initiative funded with
-
interdisciplinary backgrounds and expertise to foster cutting-edge research with high clinical relevance. Project Description Imaging methods such as magnetic resonance imaging (MRI), computed tomography (CT), and
-
life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health
-
) program. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular
-
of researchers (senior scientists, post-doctoral fellows, graduate students and research engineers) with different areas of expertise. The research program is multidisciplinary with competence in computational
-
) programme and research school Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures
-
, within the Centre for Image Analysis at the Department of IT and conducted alongside researchers developing computational methods with a particular focus on deep learning and image analysis. The project
-
, computational modelling, bioinformatic analysis, and experimental vascular biology. Based in a dynamic translational research environment of data-driven life science, computational imaging, and vascular surgery
-
collaborations. The research group The position is in Ben Murrell’s group in MTC, based in the Biomedicum, in Karolinska’s Solna campus. The lab has worked across the experimental/computational interdisciplinary
-
, integrating microfabrication, cell component and biomaterial incorporation, staining of specific biological features, and computational modelling of intrinsic properties. The evaluation of results and further