13 data-"https:" "https:" "https:" "https:" "https:" "https:" "Helmholtz Zentrum Geesthacht" Postdoctoral positions at SciLifeLab
Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
own assignments with minimal supervision. Research environment The Dwibedi lab is part of the SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS; https://www.scilifelab.se
-
spectroscopy. The scholarship is two years full time with access 15 April, 2026 or by agreement. The deadline for applications is 20 February, 2026. Departmental specific information The scholarship is placed
-
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
-
the Center for the Human Past. Thee research environment is international, with English as the working language. For more information on the Human Evolution Program, visit: https://www.uu.se/en/department
-
School of Engineering Sciences at KTH Job description The AICell Lab (https://aicell.io ) in the department of Applied Physics at KTH and Science for Life Laboratory is a research group funded by
-
the lab and bioinformatic/statistical analyses of next-generation sequence data. The project will be conducted in collaboration with Prof. Göran Arnqvist (Evolutionary Biology Centre, Uppsala University
-
(http://www.testalab.org ) in Stockholm as a Research engineer. The position focuses on the investigation of different cellular process with super-resolution microscopy to quantitatively study dynamics in
-
checks. Both parts are meant to support data-driven computational modeling for applications in epidemics. For a further description of the proposed project, see this document. The Department
-
). 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