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supervisors, you will conduct independent scientific research resulting in a dissertation. You will be accommodated at the Groningen Graduate School of Law (GGSL). The GGSL offers a training program to help
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academic research groups with expertise in experimental catalyst development and theoretical groups skilled in computational chemistry and data-driven approaches to develop new catalytic asymmetric reactions
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(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
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PhD Position: Activating Heritage as a Mediator for Dialogue and Belonging in an Era of Polarization
successful completion of the PhD thesis within the contract period is to be expected. A PhD training program is part of the agreement and the successful candidate will be enrolled in the Graduate School
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for realizing challenging asymmetric catalytic methods. This network brings together academic research groups with expertise in experimental catalyst development and theoretical groups skilled in computational
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-year PhD program, you will join a collaborative research team applying cutting-edge methods from Experimental/Behavioral Economics alongside modern macroeconomic modelling techniques (e.g. DSGE). You'll
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in collaboration with diverse partners and stakeholders, contributing not only to academic output but also to visible societal change. The PhD project is part of the “Wad Gaat Om” program, which aims
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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
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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
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Engineering, Computational Physics, Materials Science or a related discipline is required, with experience in atomistic modelling of materials and machine learning. Experience in atomistic modelling (molecular