Synoptix is delighted to announce that it is funding a PhD with King’s College London, and specifically with the Digital Twins for Health Centre for Doctoral Training, entitled “Mining Processes to Understand Real Time Decision Deltas in a UK Healthcare Department”. The project aims to blend domain-specific modelling, healthcare process mining, agent-based simulation, and data visualisation to allow healthcare decision makers to effectively engage with real-time data.
The PhD candidate will be supervised by two excellent academics from King’s College London, along with an industry co-supervisor from Synoptix.
Dr Steffen Zschaler: Dr Zschaler is an expert in software engineering, specifically model-driven engineering (MDE). MDE research focuses on the study and development of modelling theory and tools, which is key to the present project. He has previously developed modelling languages for capturing healthcare processes around patient flow in emergency care, leading to predictive simulations as part of digital twins. He will contribute his expertise in modelling languages and tools, including the modelling and simulation of processes and change-impact analysis, to this project.
Professor Richard Dobson: Professor Dobson is a Professor in Medical and Bioinformatics and his research is motivated by the integration of genomics data with data derived from patient records and mobile health for better understanding of the complex interplay between mental and physical health. He is the Informatics Lead at the National Institute of Health Research Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust and co-leads the Centre for Translational Informatics (ctiuk.org), supporting delivery of novel informatics-driven interventions into routine care. Prof Dobson co-leads the Health Data Research UK (HDR UK) National Text Analytics Programme, where their team focused on the standardisation, dissemination, and implementation of AI and Natural Language Processing (NLP) tools within the NHS; and is the academic lead for the technology components of a number of European Commission’s Innovative Medicine Initiative’s (IMI) programmes. He is also the Head of Department of Biostatistics and Health Informatics and co-Director of the King's EPSRC Data-driven Health (DRIVE-Health) Centre for Doctoral Training.
Digital twins of healthcare systems have huge potential to transform operations and outcomes, however, this is limited by challenges in implementation. Digital twins of healthcare systems require a good integration of real-world data with structured models – for example, of processes undertaken on a hospital ward. However, real-world process data is messy, does not necessarily match the structured process models expected to be implemented, and changes over time as staff adapt to changing demand pressures, policies, and temporary system faults. It is paramount that decision makers are able to engage with this real-world data, have efficient ways of identifying and predicting significant changes and variations in processes – for example as a result of proposed policy change – and can understand the impact of behaviour changes on overall system properties. This project will explore the combination of domain-specific modelling, healthcare process mining, agent-based simulation, and data visualisation to address these challenges.
To find out more about the CDT, or apply, please visit here: https://www.kcl.ac.uk/research/dt4health-cdt. Applications close on Friday 3rd January at 23:59 GMT.
For the full description of the project, please visit here: https://preview-kcl.cloud.contensis.com/nmes/assets/project-zschaler.dobson.cockburn.pdf
Synoptix to Fund Digital Twin for Health Care PHD
Synoptix is delighted to announce that it is funding a PhD with King’s College London, and specifically with the Digital Twins for Health Centre for Doctoral Training, entitled “Mining Processes to Understand Real Time Decision Deltas in a UK Healthcare Department”. The project aims to blend domain-specific modelling, healthcare process mining, agent-based simulation, and data visualisation to allow healthcare decision makers to effectively engage with real-time data.
The PhD candidate will be supervised by two excellent academics from King’s College London, along with an industry co-supervisor from Synoptix.
Dr Steffen Zschaler: Dr Zschaler is an expert in software engineering, specifically model-driven engineering (MDE). MDE research focuses on the study and development of modelling theory and tools, which is key to the present project. He has previously developed modelling languages for capturing healthcare processes around patient flow in emergency care, leading to predictive simulations as part of digital twins. He will contribute his expertise in modelling languages and tools, including the modelling and simulation of processes and change-impact analysis, to this project.
Professor Richard Dobson: Professor Dobson is a Professor in Medical and Bioinformatics and his research is motivated by the integration of genomics data with data derived from patient records and mobile health for better understanding of the complex interplay between mental and physical health. He is the Informatics Lead at the National Institute of Health Research Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust and co-leads the Centre for Translational Informatics (ctiuk.org), supporting delivery of novel informatics-driven interventions into routine care. Prof Dobson co-leads the Health Data Research UK (HDR UK) National Text Analytics Programme, where their team focused on the standardisation, dissemination, and implementation of AI and Natural Language Processing (NLP) tools within the NHS; and is the academic lead for the technology components of a number of European Commission’s Innovative Medicine Initiative’s (IMI) programmes. He is also the Head of Department of Biostatistics and Health Informatics and co-Director of the King's EPSRC Data-driven Health (DRIVE-Health) Centre for Doctoral Training.
Digital twins of healthcare systems have huge potential to transform operations and outcomes, however, this is limited by challenges in implementation. Digital twins of healthcare systems require a good integration of real-world data with structured models – for example, of processes undertaken on a hospital ward. However, real-world process data is messy, does not necessarily match the structured process models expected to be implemented, and changes over time as staff adapt to changing demand pressures, policies, and temporary system faults. It is paramount that decision makers are able to engage with this real-world data, have efficient ways of identifying and predicting significant changes and variations in processes – for example as a result of proposed policy change – and can understand the impact of behaviour changes on overall system properties. This project will explore the combination of domain-specific modelling, healthcare process mining, agent-based simulation, and data visualisation to address these challenges.
To find out more about the CDT, or apply, please visit here: https://www.kcl.ac.uk/research/dt4health-cdt. Applications close on Friday 3rd January at 23:59 GMT.
For the full description of the project, please visit here: https://preview-kcl.cloud.contensis.com/nmes/assets/project-zschaler.dobson.cockburn.pdf
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Synoptix to Fund Digital Twin for Health Care PHD
Synoptix is delighted to announce that it is funding a PhD with King’s College London, and specifically with the Digital Twins for Health Centre for Doctoral Training, entitled “Mining Processes to Understand Real Time Decision Deltas in a UK Healthcare Department”. The project aims to blend domain-specific modelling, healthcare process mining, agent-based simulation, and data visualisation to allow healthcare decision makers to effectively engage with real-time data.
The PhD candidate will be supervised by two excellent academics from King’s College London, along with an industry co-supervisor from Synoptix.
Dr Steffen Zschaler: Dr Zschaler is an expert in software engineering, specifically model-driven engineering (MDE). MDE research focuses on the study and development of modelling theory and tools, which is key to the present project. He has previously developed modelling languages for capturing healthcare processes around patient flow in emergency care, leading to predictive simulations as part of digital twins. He will contribute his expertise in modelling languages and tools, including the modelling and simulation of processes and change-impact analysis, to this project.
Professor Richard Dobson: Professor Dobson is a Professor in Medical and Bioinformatics and his research is motivated by the integration of genomics data with data derived from patient records and mobile health for better understanding of the complex interplay between mental and physical health. He is the Informatics Lead at the National Institute of Health Research Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust and co-leads the Centre for Translational Informatics (ctiuk.org), supporting delivery of novel informatics-driven interventions into routine care. Prof Dobson co-leads the Health Data Research UK (HDR UK) National Text Analytics Programme, where their team focused on the standardisation, dissemination, and implementation of AI and Natural Language Processing (NLP) tools within the NHS; and is the academic lead for the technology components of a number of European Commission’s Innovative Medicine Initiative’s (IMI) programmes. He is also the Head of Department of Biostatistics and Health Informatics and co-Director of the King's EPSRC Data-driven Health (DRIVE-Health) Centre for Doctoral Training.
Digital twins of healthcare systems have huge potential to transform operations and outcomes, however, this is limited by challenges in implementation. Digital twins of healthcare systems require a good integration of real-world data with structured models – for example, of processes undertaken on a hospital ward. However, real-world process data is messy, does not necessarily match the structured process models expected to be implemented, and changes over time as staff adapt to changing demand pressures, policies, and temporary system faults. It is paramount that decision makers are able to engage with this real-world data, have efficient ways of identifying and predicting significant changes and variations in processes – for example as a result of proposed policy change – and can understand the impact of behaviour changes on overall system properties. This project will explore the combination of domain-specific modelling, healthcare process mining, agent-based simulation, and data visualisation to address these challenges.
To find out more about the CDT, or apply, please visit here: https://www.kcl.ac.uk/research/dt4health-cdt. Applications close on Friday 3rd January at 23:59 GMT.
For the full description of the project, please visit here: https://preview-kcl.cloud.contensis.com/nmes/assets/project-zschaler.dobson.cockburn.pdf
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