Paper accepted at CICM 2022
Our paper, “Re-imagining the Isabelle Archive of Formal Proofs” (MacKenzie, Huch, Vaughan and Fleuriot), has been accepted at the 15th Conference on Intelligent Computer Mathematics (CICM 2022).
Our paper, “Re-imagining the Isabelle Archive of Formal Proofs” (MacKenzie, Huch, Vaughan and Fleuriot), has been accepted at the 15th Conference on Intelligent Computer Mathematics (CICM 2022).
Our submission on “Building co-morbidity networks via Bayesian network reconstruction” (Romero Moreno, Restocchi and Fleuriot), based on ongoing work done as part of the AI and Multimorbidity (AIM-CISC) project has been accepted as a regular talk at Complex Networks 2022, which will be held in Palermo, Italy in November.
Applications are invited for a Research Associate in Formal Modelling for Health and Care in the School of Informatics, University of Edinburgh. More information available here.
📢 PhD with Integrated Study in Advanced Care
📅 Deadline: 26 Nov 2021 (rolling)
👉 Apply here
An exciting opportunity for a interdisciplinary PhD in a fully-funded, integrated, 4-year programme at the Advanced Care Research Centre (ACRC) Academy (http://edin.care/academy). More information is available here.
Congratulations to Callum Abbott whose thesis “To Drain or Not to Drain? A Causal Investigation into the Efficacy of Subdural Drains in Preventing CSDH Recurrence” came top for the MSc in Statistics with Data Science in the School of Mathematics.
The work was supervised by Jacques Fleuriot in collaboration with Paul Brennan and Michael Poon.
We are looking for an experienced researcher (Grade 8, salary £42,149-£50,296), with a PhD in Artificial Intelligence, machine learning or data science, to coordinate and support the delivery of our core AI research programme and well as overarching programme management. This a joint post between the School of Medicine and the School of Informatics at the University of Edinburgh.
Artificial Intelligence and Multimorbidity: Clustering in Individuals, Space and Clinical Context (AIM-CISC) is a 3 year, £3.9 million research programme funded by the National Institute for Health Research (NIHR) Artificial Intelligence for Multiple Long-Term Conditions Programme. AIM-CISC is led by a multidisciplinary team from The University of Edinburgh, University College London and NHS Lothian. This includes clinical and genetic researchers studying complex multimorbidity, public partners, social scientists researching wider social and spatial determinants of health and care, and informatics and data science academics with AI expertise across multiple domains including natural language processing, machine-learning including multilayer network analysis, and applied AI.
Our formalisation of Schutz’ Independent Axioms for Minkowski Spacetime is now available in Isabelle’s Archive of Formal Proof. More information and the theories are available here.
The Luxembourg Fonds Nationals de Recherche (National Research Fund) has awarded an AFR to Richard Schmoetten to carry out his PhD research, under the supervision of Jacques Fleuriot, on “Formalising Haag-Kastler Nets in Higher-order Logic”. The work will be carried out in the proof assistant Isabelle.
Applications are invited for 3 Research Associates in Machine Learning for Health, Network Science, Knowledge Representation and AI to work within the Artificial Intelligence and Multimorbidity: Clustering in Individuals, Space and Clinical Context (AIM-CISC) programme in the School of Informatics and Usher Institute, University of Edinburgh.
Artificial Intelligence and Multimorbidity: Clustering in Individuals, Space and Clinical Context (AIM-CISC) is a 3 year, £3.9 million research programme funded by the National Institute for Health Research (NIHR) Artificial Intelligence for Multiple Long-Term Conditions Programme. AIM-CISC is led by a multidisciplinary team from The University of Edinburgh, University College London and NHS Lothian. This includes clinical and genetic researchers studying complex multimorbidity, public partners, social scientists researching wider social and spatial determinants of health and care, and informatics and data science academics with AI expertise across multiple domains including natural language processing, machine-learning including multilayer network analysis, and applied AI. The research areas are broadly as follows:
1.Network Science for the analysis and prediction of multimorbidity.
2. Machine Learning for clustering of complex multimorbidity.
3. Knowledge Representation for Medical Artificial Intelligence