Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
apply cutting-edge microscopy techniques to measure pigment behavior under realistic production and application conditions. By characterizing interactions at the nano- and microscale, you will develop
-
for delta adaptation and development under uncertain changing conditions? How can we sequence measures that are made in different regions, e.g. using modelling tools? What is the timing of decisions and what
-
’, i.e. policies that deal with problems after they occur, rather than long-term prevention. By developing innovative simulation models that incorporate the life-course consequences of policy options, your
-
investigates diagnostics and treatment for patients with an acute cerebral infarction or cerebral haemorrhage. This vacancy focuses on developing organisational models for acute neurovascular disorders
-
36-hour week. Lots of options when it comes to secondary employment conditions; we can, for example, discuss options for a sabbatical or paid parental leave. Within our terms of employment individual
-
and have access to state-of-the-art industry experts, data and knowledge, allowing you to make an impact during your PhD research. In this position you will work with real world data and models, aimed
-
to characterize the molecular properties of catalysts together with statistical methods to derive predictive models for selective catalysis. In a data-driven approach, an initial set of reactions is analyzed and
-
to train an AI model that predicts the cis-regulatory code for synthetic genomes (i.e. for cell-free gene expression systems) and correlates the experimental conditions within the synthetic cell
-
Sciences, Pedagogics or a related discipline. You have strong analytical skills and experience with complex quantitative analytical methods (e.g. multilevel and/or structural equation models). You are
-
diseases, and how these influence, or are influenced by, labor force participation and income. In addition, you will develop simulation models to predict how different policies could reduce the disease