Sort by
Refine Your Search
-
explicitly request that you refrain from including photographs/photos in your application. Application documents sent by post will not be returned; they will be destroyed after the completion of the process
-
reconstruction framework Validation of the developed dual-tracer PET imaging methods on clinical PET phantom data Collaborating closely with our scientific and clinical project partners throughout all project
-
digitalized society, a climate-friendly energy system, and a resource-efficient economy. We combine natural, life, and engineering sciences in the fields of information, energy, and bioeconomy with specialist
-
January 14, 2026: https://www.uni-goettingen.de/de/application/556704.html Applicants will be asked to upload a CV, academic records (as PDFs), and contact information for two referees. You may select up
-
the application you agree that your personal data will be shared among the participating institutions (University of Tubingen, University of Hohenheim, Senckenberg) for the purpose and over the duration
-
. The successful candidate should have experience with advanced astrophysical data analysis in the context of multi-mission and multi-wavelength observations including e.g., Fermi-LAT and imaging X-ray
-
to mastering the great challenges facing society today. The Center for Advanced Systems Understanding (CASUS) is a German-Polish research center for data-intensive digital systems research. The Department
-
network analyses experience is useful Experience in data analysis and scientific publication Ability to work in a team, good English communication skills A driver licence is useful Our offer We offer
-
-wide network in microbiome science For further information please contact Prof. Holger Sondermann at +49 40 8998‑87680 ( holger.sondermann at cssb-hamburg.de ). DESY in Hamburg does not grant doctoral
-
infectious diseases, antimicrobial resistance, medical decision making and population health metrics. Interest and experience in empirical applications of economic theory, the analysis of large health data