Sort by
Refine Your Search
-
Employer
-
Field
-
). The project focuses on developing computational models for cancer risk assessment, integrating multiple types of data and risk factors. The main objective is to design and apply machine learning and deep
-
Arctic headwaters. It will include field studies and the use of existing data, potentially complemented with modelling. The postdoc is also expected to collaborate with project partners and carry out
-
interdisciplinary research environment More information about Jönköping University as a workplace, conditions and benefits on www.ju.se . Required Qualifications Applicants must have been awarded a PhD in Computer
-
for further development. The postdoctoral position includes a combination of experimental work, data analysis, as well as interpretation and presentation of research results. The main part of the work for the
-
evaluated and validated using uniquely integrated historical datasets comprising environmental, social, demographic, mobility, and epidemiological information. The successful candidate will contribute to a
-
, 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
-
working with associated techniques, such as bioprinting, is considered an asset. To be eligible for the position, the applicant must be able to analyze and interpret data, have excellent oral and written
-
techniques such as SEM, TEM, XRD, EDS, EBSD, FIB/SEM etc., as well as physico-mechanical characterization techniques such as tensile, compression, DSC/TGA, etc. as well as analysis of the data with good
-
ovarian cancer and accompanying biomarkers for guiding personalized therapy. Work duties The main duty is to conduct research within the subject area, including experimental work, data analysis
-
of Gothenburg in Sweden and the Norwegian Institute of Public Health (Oslo). We investigate genetic and environmental factors affecting human gestational age at pre-term birth. We work with unique genomic data