-
the Concordat to Support the Career Development of Researchers , applies to Postdocs, Research Assistants, Research and Teaching Technicians, Teaching Fellows and AEP equivalent up to and including grade 7
-
development. This entitlement, from the Concordat to Support the Career Development of Researchers, applies to Postdocs, Research Assistants, Research and Teaching Technicians, Teaching Fellows and AEP
-
are entitled to at least 10 days per year (pro-rata) for professional development. This entitlement, from the Concordat to Support the Career Development of Researchers , applies to Postdocs, Research Assistants
-
high content imaging, multimodality in vivo imaging, proteomics, spatial and single-cell transcriptomics. As part of King’s Health Partners, we have an excellent environment for basic-clinical
-
are entitled to at least 10 days per year (pro-rata) for professional development. This entitlement, from the Concordat to Support the Career Development of Researchers, applies to Postdocs, Research Assistants
-
in sustainability, photonic and quantum technologies, new nanostructured materials, sensing, imaging and clean energy. The group adopts an interdisciplinary approach to provide leading-edge research in
-
to Postdocs, Research Assistants, Research and Teaching Technicians, Teaching Fellows and AEP equivalent up to and including grade 7. Visit the Centre for Research Staff Development for more information
-
to Postdocs, Research Assistants, Research and Teaching Technicians, Teaching Fellows and AEP equivalent up to and including grade 7. Visit the Centre for Research Staff Development for more information. About
-
. This entitlement, from the Concordat to Support the Career Development of Researchers , applies to Postdocs, Research Assistants, Research and Teaching Technicians, Teaching Fellows and AEP equivalent up to and
-
fluorescence-lifetime detection (Fast-FLIM) and temporal focusing. This instrument will deliver quantitative, sub-second imaging of live three-dimensional cell-culture and organoid models, advancing fundamental