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PhD Studentship in Workflow management meets the Internet of Things

Project Description

Digital workflows are models of coordination patterns for collaborative human and computer agents. They help streamline and optimize processes by clarifying standard practices, automating administrative tasks, monitoring progress in real-time, and providing predictive analysis and decision support.

IoT devices and sensors, for their part, can provide real-time, heterogeneous data that fully describe the current state of people, assets, machines, computers, resources, etc. at any given time, with little human intervention. Combining workflow management with such data can lead to a highly contextualized, complete view of the operations in any collaborative environment, as well as key insights for optimization and prediction.

The aim of the project is to research the integration of IoT data streams into different stages of the workflow lifecycle. This involves filtering, analysing, fusing and contextualising low level sensor data to generate high level event logs using both symbolic (rule-based) and statistical AI techniques. The project will be focused on the particular context of workflow management, including process mining, live monitoring, and conformance checking.

The candidate will also have the opportunity to apply their research in real-world problems, in collaboration with stakeholders from the industry and public sectors. Examples of application areas include but are not limited to:

- Patient pathways for health and social care
- Manufacturing flows for Industry 4.0
- Construction and public infrastructure
- Business process, workforce and supply chain management

Candidate’s profile

- A Masters degree with Distinction (or a First Class honours BSc in exceptional cases) from a leading UK university or equivalent overseas qualification in computer science, artificial intelligence, mathematics, or other related subject.
- Strong analytical and programming skills.
- Good understanding/knowledge/experience in at least one of the following areas: workflow management, complex event/stream processing, logic-based reasoning (including model checking), process modelling/mining, sensor fusion
- Keen and demonstrable interest in at least one of the application areas is also desirable.

Funding Notes

The studentship covers:

• Full time PhD tuition fees for a student with UK/EU nationality (£4,327 per annum, subject to annual increment).
• A tax-free stipend of GBP £15,009 per year for 3.5 years.
• Additional programme costs of £1000 per year.

Related Subjects

How good is research at University of Edinburgh in Computer Science and Informatics?

FTE Category A staff submitted: 94.85

Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities

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