-
networks. This position is part of a UK-Canada Quantum for Science collaborative project "Quantum network applications in theory and practice" funded by STFC/EPSRC (UK) and NSERC (Canada), led by Professor
-
to ionising radiation and clinically relevant drugs. A strong focus of this research is to study the specific functions of key DNA repair enzymes in high detail, how they function as a network to facilitate
-
modelling of the C. elegans neural network. The lab also uses Two Electrode Voltage Clamp (TEVC) electrophysiology and molecular biology techniques to characterise receptors. There are a broad range of
-
-leading physics capabilities and enable time-dependent, non-LTE radiative transfer magnetohydrodynamic (MHD) simulations. The framework will be released as open-source software, with a strong emphasis on
-
broad aims of the group are to develop statistical methods, run applied analyses that address important clinical questions, and disseminate methods in the area of Mendelian randomization, defined as the
-
pipelines will include structural imaging, multi-shell diffusion, susceptibility weighted imaging and functional MRI. These analyses will make use of publicly available tools, and may also require software
-
well as in designing coordination strategies for them. Our recent work on RL and graph neural networks (GNNs) demonstrate some of our key research directions relevant for this position. A high degree of self
-
interdisciplinary collaboration. The candidate will have the opportunity develop a large network of research collaborators based at universities and non-governmental organizations. The work is on site. There will be
-
will assist with high-throughput CRISPR-Cas9 screens to explore sensitivity/resistance mechanisms in defined genetic backgrounds, followed by validation and ensuing mechanistic studies. Experience in
-
metabolism and human physiology. Experience with clinical research and/or experimental medicine studies necessary. Analytical Skills: Proficiency in data analysis and statistical software. Experience with high