Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- UTB
- Tilburg University
- Fraunhofer-Gesellschaft
- Technical University of Denmark
- ETH Zurich
- University of Oslo
- AALTO UNIVERSITY
- Aalborg University
- Aalto University
- European Space Agency
- Harvard University
- Heinrich Heine University Düsseldorf
- Helmholtz Association of German Research Centres
- Inria
- King's College London
- Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V.
- Linköping University
- Mayo Clinic
- Nanyang Technological University
- National University of Singapore
- Rosalind Franklin Institute
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- SciLifeLab
- Singapore Institute of Technology
- Technische Universität Dresden (TU Dresden)
- The Chinese University of Hong Kong, Shenzhen
- The University of Auckland
- University of Copenhagen
- University of Florida
- University of Lincoln
- University of Maryland, Baltimore
- University of Sheffield
- University of Southern Denmark
- University of Twente
- 24 more »
- « less
-
Field
-
project combines advanced 2D and 3D bioimaging, including micro/nanoCT, confocal microscopy and SEM, with computational image analysis, computer vision and machine learning. The aim is to develop robust
-
, imaging, computation, and AI. Molecular Perturbations: Chemistry Engineering Biology Criteria: A strong background in chemistry, biochemistry or related disciplines with passion to design and apply
-
degree Programming skills (Python) and experience with common machine learning platforms Experience with deep learning, computer vision, medical image analysis or unsupervised learning is an advantage
-
internationally recognised academic environment with over 400 employees and 10 research sections. We broadly cover digital technologies within mathematics, data science, computer science, and computer engineering
-
from 1 Dec 2026 (flexible start date). Funding is provided for up to four years. Applicants should hold an MSc degree and have a strong background in computer science, engineering, mathematics, physics
-
electrical engineering, computer science or a closely related field. A solid foundation in computer vision, pattern recognition, AI-related techniques. Hands-on interest in designing methods using
-
research/professional experience) in computer science, machine learning, medical imaging, biomedical engineering, data science or a closely related discipline. Essential Application/interview Strong
-
UTB | about 1 month ago
using physically grounded image data. The research explores how AI-driven analysis can move beyond manual reverse-engineering workflows by automating feature extraction and structural interpretation
-
UTB | about 1 month ago
using physically grounded image data. The research explores how AI-driven analysis can move beyond manual reverse-engineering workflows by automating feature extraction and structural interpretation
-
UTB | about 1 month ago
using physically grounded image data. The research explores how AI-driven analysis can move beyond manual reverse-engineering workflows by automating feature extraction and structural interpretation