Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Technical University of Munich
- Technical University of Denmark
- ;
- Curtin University
- Hannover Medical School •
- Nature Careers
- Swinburne University of Technology
- University of Sheffield
- ; City St George’s, University of London
- Erasmus MC (University Medical Center Rotterdam)
- Erasmus MC (University Medical Center Rotterdam); Rotterdam
- Forschungszentrum Jülich
- Institut Pasteur
- KINGS COLLEGE LONDON
- Monash University
- Trinity College Dublin
- UiT The Arctic University of Norway
- University of Adelaide
- University of Utah
- VIB
- ; St George's, University of London
- ; Swansea University
- ; University of Warwick
- Canadian Association for Neuroscience
- Cranfield University
- Crohn’s & Colitis Australia IBD PhD Scholarship
- DAAD
- Dresden University of Technology •
- East Carolina University
- Eindhoven University of Technology (TU/e)
- Human Technopole
- Imperial College London
- KNAW
- KU LEUVEN
- Leibniz
- Loughborough University
- Radboud University Medical Center (Radboudumc)
- Radboud University Medical Center (Radboudumc); Nijmegen
- Technische Universität Berlin •
- The Ohio State University
- The University of Iowa
- University of Alaska
- University of Amsterdam (UvA)
- University of Amsterdam (UvA); Amsterdam
- University of Antwerp
- University of Birmingham
- University of Groningen
- University of Luxembourg
- University of Minnesota
- University of North Carolina at Chapel Hill
- University of Nottingham
- University of Tübingen •
- University of Warwick
- 43 more »
- « less
-
Field
-
for medical imaging, tailored for deep learning. The high-level goal of the project is simple: to use anatomical knowledge and existing knowledge as training data for deep neural networks (instead of manual
-
global change, damaging critical infrastructure resilience. This project is part of the prestigious Loughborough University Vice Chancellor’s PhD Cluster – RAINDROP (Resilient eArthwork INfrastructure
-
annotations are scarce or unreliable. Recently developed unsupervised learning methods allow to circumvent this limitation by learning patterns in unlabelled medical images and then leveraging them
-
for high-energy X-rays, thermal instability, or issues related to toxicity and cost. As imaging demands increase—particularly in fields like high-throughput synchrotron science, medical diagnostics, and
-
“PhD relocation to Denmark and startup “Zoom” seminar ” for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU. Application procedure Your complete online
-
Funding for: UK/Home Students We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available
-
important question to solve, as DNA damage-stalled RNA polymerase causes bigger problems for the cells than the actual DNA damage itself. In this project we will use innovative single molecule imaging
-
, Biomedical Sciences, Molecular Sciences, Nanobiology). Experience with the basal transcription process, DNA damage response or with live cell imaging and microscopic data analysis is an advantage but not
-
focus on understanding how axons maintain their structure and function, and how these processes break down in disease. You will have the opportunity to contribute to one of our ongoing projects addressing
-
efficient for medicine? If the answer is yes, please continue reading! Join our team! We are looking for a PhD student to work on the topic of shape analysis for medical imaging, tailored for deep learning