Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
physics, electrical engineering, image processing, computer vision, AI, machine learning, data science, computer science, applied mathematics, or in a similar field, or have completed at least 240 credits
-
to demonstrate documented proficiency in English. You have knowledge and expertise in computer vision and/or medical image analysis, deep learning as well as mathematics. You have substantial expertise in
-
to demonstrate documented proficiency in English. You have knowledge and expertise in computer vision and/or medical image analysis, deep learning as well as mathematics. You have substantial expertise in
-
. Experience in deep learning, computer vision, or neural network development. Experience with live-cell microscopy, fluorescence microscopy, or analysis of 3D/4D image data. Experience in cell biological
-
At the department, education is conducted in the subjects of computer engineering, electronics, electrical engineering and sound production. The research at the department takes place at
-
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 processes
-
on primary brain tumors. The Wittrup group works with a range of techniques to improve RNA delivery to tumors, as well as developing methods to study and characterize these processes. Within the research group
-
% Start date: July 2026, or otherwise agreed Are you a student with a keen interest in single molecule technology and a passion for applying your skills to characterize molecular interactions to support
-
application! We are looking for a PhD student in biomedical engineering with a focus on deep learning for medical images Your work assignments The position focuses on developing methods for federated learning
-
for therapy. To do this, we interrogate the spatial relationships between B and T cell clones and their immediate niches within tissues using our in-house developed spatial transcriptomics-based technology