DPhil in Computational Discovery Philip Fowler, 23rd January 202323rd January 2023 I have a project advertised as part of the DPhil in Computational Discovery programme at the University of Oxford to start in October 2023. This programme is jointly run with IBM and benefits from their applied research in machine learning and other shared areas of interest. The project (Project 6) aims to develop graph-based convolutional machine learning methods able to integrate protein structure, genetic, chemical and evolutional information and thence predict if specific alleles confer resistance to one (or more) antibiotics. If that sounds interesting and you’d like to study it for your DPhil (i.e. PhD) with me, please apply to the programme directly as all applications are handled centrally. Applications close on 1 March 2023. Share this: Share on X (Opens in new window) X Share on Bluesky (Opens in new window) Bluesky Email a link to a friend (Opens in new window) Email Share on LinkedIn (Opens in new window) LinkedIn Share on Mastodon (Opens in new window) Mastodon Related group
group Alice Brankin wins NDM Prize 18th November 202118th November 2021 Congratulations to Alice who last night was awarded an NDM prize for the work she’s… Share this: Share on X (Opens in new window) X Share on Bluesky (Opens in new window) Bluesky Email a link to a friend (Opens in new window) Email Share on LinkedIn (Opens in new window) LinkedIn Share on Mastodon (Opens in new window) Mastodon Read More
group Congratulations Dr Adlard! 7th March 202612th March 2026 Dylan successfully defended his DPhil on Friday 6 March, well done. From what he said… Share this: Share on X (Opens in new window) X Share on Bluesky (Opens in new window) Bluesky Email a link to a friend (Opens in new window) Email Share on LinkedIn (Opens in new window) LinkedIn Share on Mastodon (Opens in new window) Mastodon Read More
antimicrobial resistance New preprint: Predicting pyrazinamide resistance in M. tuberculosis using a graph convolutional network 29th October 202530th October 2025 In previous work we’ve used “traditional” machine-learning approaches, like XGBoost, to learn and therefore predict… Share this: Share on X (Opens in new window) X Share on Bluesky (Opens in new window) Bluesky Email a link to a friend (Opens in new window) Email Share on LinkedIn (Opens in new window) LinkedIn Share on Mastodon (Opens in new window) Mastodon Read More