Sort by
Refine Your Search
-
Category
-
Program
-
Employer
-
Field
-
of Health Science and Technology, one or more PhD stipends in Unsupervised Learning for Medical Image Analysis are available for appointment from November 1, 2026, or as soon as possible thereafter
-
hospitals in the Central Denmark Region. We have approx. 30,000 square metres of modern research facilities for experimental surgery and medicine, animal facilities and also advanced scanners at our disposal
-
deep learning, computer vision, medical image analysis or unsupervised learning is an advantage. English language skills, both written and spoken Qualification requirements PhD stipends are allocated
-
1.1.2027 or as soon as possible. Job description You will be contributing to/establishing/developing an in-situ imaging system for NH3. You will be further developing optical NH3 sensors in the laboratory
-
pumping technologies for future electrified energy systems. We are currently recruiting a PhD candidate at DTU for a project on the multi-physics modelling of bearingless pumps. A parallel PhD position is
-
other relevant stakeholders. The PhD student will contribute to the prototype development, feasibility test and evaluation of innovative cross-sectoral pathways and will be involved in data collection
-
to the operation, development, and maintenance of laboratory infrastructure across the department. The position involves collaboration with researchers, students, and technical staff in a broad range of experimental
-
, data management and analysis (under supervision) performing research tasks within the area of classical archaeology, e.g. literature searches and image processing supporting processes in connection with
-
take approaches combining mouse developmental genetics, cell-type-specific viral tracing, ex vivo electrophysiology, opto/chemogenetics, in vivo imaging, single-nucleus RNA sequencing (snRNA-seq), and
-
O-PTIR, Raman, and fluorescence imaging methods. Analyze micro- and nanoplastics in biological and environmental samples. Process spectral and imaging data using chemometrics and multivariate