Sort by
Refine Your Search
-
the model, its numerical implementation in a finite element code, and its validation against experimental data in collaboration with experimental collaborators. You will also engage with the hub activities
-
Applications are invited for a Postdoctoral Research Assistant who will develop and implement predictive many-body theoretical methods to understand exciton scattering and dissociation dynamics in
-
an important component of the research support available at the School. The RAST sits within the School’s Research Office and is managed by the Head of Research Support and Administration. The successful
-
computational and experimental mechanistic studies to drive (pre)catalyst and methods development for carbon-carbon and carbon-heteroatom bond forming reactions. Find out more about Professor Neidig’s research
-
successful delivery of the qualitative component of the project. You will contribute to the design of qualitative research materials, and applications for regulatory approvals. You will also support child
-
and clinical neuroscience. This project involves development of machine learning methods for mapping the relationships between diffusion MRI (dMRI) and phase-sensitive OCT (PS-OCT) in the same tissue
-
. This can involve IoT connected devices, physical sensors or other instruments, including non-intrusive methods and inferences from a variety of data sources. You should have some experience with experimental
-
and how they contribute to cell heterogeneity. An important component of the studies will be to use advanced cell imaging, including confocal and super-resolution modalities such as d-STORM and STED
-
consortium, the research involves elements of design, novel process and equipment development, modelling, manufacture, characterisation and data science. All applications must be made online using the Oxford
-
Computational Methods for Advanced Research to Transform Biomedicine ( SMARTbiomed ), an international collaboration that integrates large-scale, multimodal biomedical data with advances in statistical and