11 image-processing-"Embry-Riddle-Aeronautical-University" Postdoctoral positions at Umeå University
Sort by
Refine Your Search
-
surgery. Description of the project and work responsibilities The project involves basic science and clinical research samples, with particular focus on the role of autologous fat in regenerative plastic
-
ecosystem processes across elevational gradients in mountains (https://www.nature.com/articles/nature21027). Following from that work, and to better understand the mechanisms involved, about a decade ago we
-
, the establishment and optimization of behavioral assays under controlled oxygen conditions, image‑based analyses, and quantitative data processing and interpretation. The role also includes active participation in
-
relevant. Our group approaches this question from a novel perspective, by studying the role of transposable elements (TEs) in this process. TEs occupy 50% of the human genome and are known to be very strong
-
for a trade union organisation or other similar circumstances, and for relevant duties/assignments within the subject area. It is meritorious if you have specific experience working with medical images
-
well as state-of-the-art mucus measurements and imaging techniques. The specific work responsibilities of the postdoctoral researcher include: · Test how specific dietary supplements affect mucus
-
The Department of Diagnostics and Intervention is looking for up to two postdoctoral research fellows for projects focusing on imaging of brain plasticity, with applications towards aging and
-
multimodal data analysis. Experience on image processing via machine learning. Programming skills (e.g., Python) are required. Ability to communicate effectively in both spoken and written English. Merits
-
imaging. The center provides access to excellent infrastructure and is well equipped with all necessary instrumentation. The laboratory has a strong background in gene regulation and 3D chromatin
-
–environment systems. A central component of the project is the development of next-generation process-based eco-epidemiological models that explicitly integrate environmental variability, ecological