52 lake-modeling Postdoctoral positions at Technical University of Denmark in Denmark
Sort by
Refine Your Search
-
industrial domains. The scientific outcomes are expected to be significant in: Earth system science – by improving models of Earth surface evolution and enabling better predictions of landscape response
-
The project’s focus will be on modeling novel silicone polymers and elastomers and developing mechanical design for storage of energy in the form of large elastic deformations. A close collaboration with chemists
-
focus on charge injection, ion transfer, and structural dynamics in realistic and model systems for battery materials. The position will span experimental efforts at large scale X-ray facilities, handling
-
the project. Your main tasks will be: Develop and apply electromagnetic modelling techniques in combination with inverse design to study light-matter interactions in dielectric nanostructured optical surfaces
-
collaboration within e.g. nutrition, chemistry, toxicology, microbiology, epidemiology, modelling, and technology. This is achieved through a strong academic environment of international top class with
-
biosolutions. The institute’s tasks are carried out in interdisciplinary collaboration within e.g. nutrition, chemistry, toxicology, microbiology, epidemiology, modelling, and technology. This is achieved
-
on regulatory mechanisms of cell signalling in several cellular models. The team combines omics technologies with bioinformatics, and functional validation of candidates by biochemical, cell biology, and imaging
-
(RAG) models – are shaping professional expertise and practice across diverse Danish public sector domains, especially among frontline workers, including caseworkers, service providers and welfare
-
proteins as food ingredients in food models Conduct project reporting and publishing results in international scientific journals Participating in teaching and supervision of students at all levels As a
-
will benefit from Lonza’s expertise and technology within peptide T cell immunogenicity, and the vast expertise within immunoinformatics and machine learning models at DTU to address this challenge