13 data "https:" "https:" "https:" "https:" "Université catholique de Louvain (UCL)" Postdoctoral research jobs at SciLifeLab
Sort by
Refine Your Search
-
on bioinformatics analysis of spatial gene expression data as well as other modalities (i.e. microbiome; metabolites, proteins) generated using the Spatial Transcriptomics (ST) method, Spatial metaTranscriptomics
-
and integrative (proteo-)omics expertise in the lab, guided by leading experts in terminomics, systems-level data analysis, and structural bioinformatics. Your profile A PhD in biology, biochemistry
-
. Salary and employment benefits The university applies individual salaries. More information about employee benefits is available https://liu.se/en/work-at-liu/employee-benefits . Union representatives
-
years according to central collective agreement. Full time position. Starting date as agreed. Placement: Uppsala For further information about the position, please contact: Ruisheng Xiong (e-mail
-
or senior staff scientist. More information: https://www.scilifelab.se/researchers/simon-koplev/ Qualifications Requirements A doctoral degree or an equivalent foreign degree. This eligibility requirement
-
of Medical Biosciences, which offers an international, collaborative, and open-minded research environment. Please visit the lab’s webpage for more information: https://erdemlab.github.io . The Erdem research
-
entitles you to several benefits through our collective agreement. Location: Solna More information https://bensonlab.se/ Application An employment application must contain the following documents in English
-
. Active participation in major international consortia. Support for career development, conference travel, and long-term academic progression More information: https://www.scilifelab.se/researchers/simon
-
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 advertised position involves studies of specific
-
). 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