Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
/Cas and degron systems) with a range of advanced functional genomics methods, particularly single-cell technologies, in pre-clinical model systems such as cell lines and patient-derived tumor organoids
-
whether each applicant is qualified and, if so, for which of the two models. The assessed applicants will have the opportunity to comment on their assessment. You can read about the recruitment process at
-
, for which of the two models. The assessed applicants will have the opportunity to comment on their assessment. You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment
-
vitro and in vivo models of immunology Experience with mRNA-based vaccines and adjuvant formulation Capable of handling a multifaceted project with many stakeholders and collaborators You are expected
-
, modularisation and platform design. Experience with Digital Advanced Product Modelling using CAD design, simulations, and mathematics. A strong motivation for collaborative projects within academia and industry
-
science applications Computational Atomic-scale Materials Design with a focus on materials modeling and discovery with electronic structure calculations and machine learning Luminescence Physics and
-
to: Perform prospective life cycle assessment of emerging technologies in the blue bioeconomy domain, specifically microalgae production Focus explicitly on quantitative approaches for consequential modelling
-
astronomy. You will be involved in the observations and modeling of extreme astrophysical phenomena, such as supernova explosions, the tidal disruptions of stars around supermassive black holes, and the
-
for resilient high-mix low-volume manufacturing. The aim of this PhD project is to enable fast setup of robot manipulators to complete advanced manufacturing tasks by the use of digital models. This should be
-
for resilient manufacturing systems. This topic will build upon existing theory on modular and reconfigurable manufacturing systems and develop methods and model-based approaches to design and evaluate resilient