Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Technical University of Munich
- SciLifeLab
- Duke University
- Nature Careers
- Swinburne University of Technology
- The University of Iowa
- ;
- Curtin University
- Hannover Medical School •
- ; City St George’s, University of London
- Chalmers University of Technology
- Forschungszentrum Jülich
- Institut Pasteur
- Monash University
- Technical University of Denmark
- The Ohio State University
- Trinity College Dublin
- University of Adelaide
- University of Antwerp
- University of Central Florida
- University of Copenhagen
- University of Minnesota
- University of Nottingham
- University of Sheffield
- University of Utah
- VIB
- ; St George's, University of London
- ; Swansea University
- ; University of Warwick
- Aalborg University
- Ariel University
- Canadian Association for Neuroscience
- Cranfield University
- Crohn’s & Colitis Australia IBD PhD Scholarship
- DAAD
- Dresden University of Technology •
- East Carolina University
- Georgetown University
- Imperial College London
- KNAW
- Leibniz
- Technische Universität Berlin •
- The University of Chicago
- UiT The Arctic University of Norway
- University of Alabama at Birmingham
- University of Alaska
- University of California, Berkeley
- University of Groningen
- University of Lethbridge
- University of Luxembourg
- University of Maryland, Baltimore
- University of Tübingen •
- 42 more »
- « less
-
Field
-
Imaging of Materials Facility (AIM ) led by Professor Richard Johnston and Swansea University's Simulation and Immersive Learning Centre (SUSIM ). The student will develop novel medically bespoke protocols
-
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 biology and healthcare; then, the Chair of Biological Imaging (CBI) at the Technical University of Munich (TUM), and its integrated Institute of Biological and Medical Imaging (IBMI) at the Helmholtz
-
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
-
to circumvent this limitation by learning patterns in unlabelled medical images and then leveraging them for downstream tasks. In this project, you will develop novel unsupervised machine learning methods
-
novel strategies to treat seizures and cytotoxic edema, especially in neonates. To reach this goal, we are addressing the following questions: 1. How does the brain inhibitory system work at the cellular
-
focus will be on biomechanics, image processing, machine learning (ML), artificial intelligence (AI), and metrology, the student will also contribute to the co-design of cadaver experiments and data
-
including predictive modelling, computer vision and epidemiology. The student will join an established team of investigators, including statisticians, epidemiologists, image scientists, and clinicians
-
international collaborations with clinicians, regulators, policymakers, and industry partners. You must have a strong background in machine learning, computer vision, and medical image analysis, with publications
-
and/or atom probe tomography Experience in image processing Experience in programming with Python or Matlab is strongly desired Team spirit as well as excellent communication and organizational skills