Data science for science projects
The Jean Golding Institute have supported a number of projects in data science for science
Optimization of ultra-thin radiation resistant composites structures for space applications
Composites have been used for space applications due to their high performance properties. However, the environmental conditions experienced during space exposure lead to severe structural damage.
EPIC Lab: Generating a first-person (egocentric) vision dataset for practical chemistry
Building on the Epic Kitchens project, a collaboration between the Schools of Computer Science and Chemistry
Enabling advanced analytics for all users of the proteomics facility
In collaboration with proteomics labs in Manchester and Liverpool, the Dowsey group developed a Bayesian model called BayesProt - the cornerstone of several large-scale translational studies.
EPIC-KITCHENS 2018: A publicly available dataset
The largest dataset in first person (egocentric) vision capturing non-scripted daily activities in peoples' kitchens over multiple days.
GPU accelerated image processing of Cryo-EM data determining a high-resolution structure of the Thermosome a molecular machine
With a trip to the National Electron Microscopy (EM) facility and the expertise of a Junior Research Software Engineer, this project built a GPU machine and cooling system
Supervised learning to support the optimisation of chemical reactions
This project explored the application of different statistical approaches to the analysis of chemical data from previous systematic experiments on a key variable (ligands) in homogeneous catalysis.
Developing a deep learning method for phylogenomics
This project developed and tested a deep learning algorithm for phylogenomics focusing particularly on programming, implementing and validating the approach.