Sort by
Refine Your Search
-
(spoken and written). Preferred qualifications Prior experience with 3D cell culture, organoids, CRISPR-Cas9, or imaging-based phenotyping. Familiarity with transcriptomics or basic computational biology (R
-
for Energy Business and Economics Research (CEnBER - https://www.rug.nl/cenber/ ) and in the research programme Economics, Econometrics & Finance of FEB’s Research Institute. The project will be supervised by
-
of the Open Competition Domain Science-M programme (Twenty-one innovative research projects awarded through Open Competition Domain Science-M programme | NWO - https://www.nwo.nl/en/news/twenty-one-innovative
-
dissecting RNA structure ensembles in living cells. Particularly, you will: Develop novel methods (both wet and computational) for the accurate interrogation of RNA 2D and 3D structures in living cells. Apply
-
working memory contents held within. Second, we will use computational spiking-neuron models to explain the results of the experiments and implement the neural mechanisms responsible. These models will also
-
on sufficient progress in the first year to indicate that a successful completion of the PhD thesis within the next three years is to be expected. A PhD training programme is part of the agreement and the
-
their appointment. Willingness to move and reside in the Netherlands. Do you want to become a member of our team? Please send your application to us, by submitting the following documents in English: Motivation
-
The Groningen Institute for Evolutionary Life Sciences (GELIFES - https://www.rug.nl/research/gelifes/ ) offers a 4-year M20 Program funded PhD position for a project on “Multi-dimensional
-
PhD thesis within the contract period is to be expected. A PhD training programme is part of the agreement and the successful candidate will be enrolled in the Graduate School of the Faculty
-
will be embedded within the research programme Marketing at the Faculty of Economics and Business (FEB). The project will be supervised by Marijke Leliveld and Kim Poldner. The ideal candidate is highly