Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Employer
- Stanford University
- Indiana University
- University of British Columbia
- MACQUARIE UNIVERSITY - SYDNEY AUSTRALIA
- NEW YORK UNIVERSITY ABU DHABI
- SciLifeLab
- Stony Brook University
- The University of Iowa
- UNIVERSITY OF HELSINKI
- University of Colorado
- University of Florida
- University of Glasgow
- University of Minnesota
- University of North Carolina at Chapel Hill
- VIB
- Yale University
- Boise State University
- CEA
- Chalmers University of Technology
- Computer Vision Center
- Dalhousie University
- Dana-Farber Cancer Institute (DFCI)
- ETH Zürich
- Eindhoven University of Technology (TU/e)
- European Space Agency
- FAPESP - São Paulo Research Foundation
- Forschungszentrum Jülich
- Harvard University
- Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt
- INSERM
- Inria, the French national research institute for the digital sciences
- Institut Pasteur
- Institute for Bioengineering of Catalonia (IBEC)
- Institute for bioengineering of Catalonia, IBEC
- KTH Royal Institute of Technology
- KU LEUVEN
- King Abdullah University of Science and Technology
- Memorial Sloan-Kettering Cancer Center
- North Carolina State University
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- The University of Arizona
- Télécom Paris
- Umeå University
- Universidade do Minho
- University College Cork
- University of California Berkeley
- University of California Irvine
- University of Illinois at Urbana Champaign
- University of Kansas Medical Center
- University of Manchester
- University of Michigan
- University of Nevada Las Vegas
- University of Oslo
- University of Oxford
- University of Texas at Arlington
- University of Texas at Austin
- University of Texas at Dallas
- University of Washington
- Universität für Bodenkultur
- Uppsala universitet
- Utrecht University
- Zintellect
- universitypositions
- Łukasiewicz Research Network – PORT Polish Center for Technology Development
- 54 more »
- « less
-
Field
-
University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 4 hours ago
world. Position Summary This Postdoctoral Research Associate will conduct advanced research in artificial intelligence, machine learning, computer vision, and medical image analysis. The position will contribute
-
foundational methods for integrating single-cell and clinical transcriptomes; and train, fine-tune, and validate deep learning models using multi-omics and imaging data to predict clinical outcomes such as
-
. Education and scholarly development The postdoctoral associate will receive structured education in computer vision applications in medical imaging, machine learning, research methodology, responsible conduct
-
for supervised and unsupervised learning. We devise deep learning models, which find application in imaging and image-based science, including in collaboration with domain scientists on and off campus in fields
-
and qualifications Expertise in advanced machine learning, deep learning and image vision techniques with focus on EO data (e.g. deep convolutional neural networks, transformers, deep learning based
-
Science, Biostatistics, or a closely related area. Strong ML/deep learning foundation plus expertise in at least one of: multimodal learning, time-series modeling, or NLP. Demonstrated working experience
-
Development of reproducible software tools and computational workflows for biomedical research Develop novel AI, machine learning, and deep learning methods to address complex biomedical questions in diabetes
-
completed a postdoctoral contract of at least 2 years and have advanced research experience in the field of microscopy and image analysis. You are an expert in cryo-electron microscopy and image analysis. You
-
Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 1 month ago
-driven technologies for biomedical research and cancer diagnostics Your profile Master's degree in a relevant field Experience in machine learning for imaging, ideally in biomedical or histopathological
-
or deep learning reconstructions). Knowledge of radial data acquisition strategies, artifact mitigation methods, and their use in parametric imaging (e.g., T1/T2/T2* mapping). Preferred Qualifications