Graduate Teaching Assistant (GTA) - Advancing the Optimisation of Simulation and Machine Learning Pi

Applications from job seekers who require sponsorship to work in the UK are welcome and will be considered alongside all other applications. However, non-UK candidates who do not already have permission to work in the UK should note that by reference to the applicable SOC code for this role, sponsorship will not be possible under the Skilled Worker Route. There is further information about this on the UK Visas and Immigration Website .

Part-time, fixed-term (4 year) role.

Closing date: 23:59 GMT 20 July 2025

Interview date: to be confirmed

We are pleased to announce a fantastic opportunity for ambitious computer scientists to join our Computer Science Graduate Teaching Assistant (GTA) Programme!

How does it work?

Candidates will study for a four year, full time funded PhD (3 quarters of your time) whilst working and receiving a salary to gain valuable teaching experience (1 quarter of your time). Candidates will receive a salary and stipend package that exceeds the standard UKRI stipend for a full-time PhD.

Home/RoI Students will have their PhD fees waived, International students will receive a fee waiver equivalent to the Home/RoI fee and will be expected to fund the difference between the International fee and the Home/RoI fee. There will be a package of support to enable you to develop a research career in this exciting field.

PhD Topic: Advancing the Optimisation of Simulation and Machine Learning Pipelines for enhanced performance benchmarked in the Healthcare Domain

The Royal Berkshire Hospital has 20 surgical theatres and only 3-4 beds for patients\’ overnight full recovery from anaesthesia. Thus to avoid exceeding the bed capacity a daily limit is imposed on those surgeries that are deemed likely to require overnight stay for post anaesthesia recovery. The needed post-operative care is predicted manually based on a pre-operative assessment for surgeries case selection to be scheduled for each day. This decision process is poorly recorded and needs improvement.

Aims and Objectives

In collaboration with the Health Innovation Partnership, a modelling pipeline will be devised to cope with the challenges of data augmentation and model optimisation to deliver a reliable prediction of patient needs into recovery services after surgery, improving the deployment of available resources, ensuring patient quality-of-care and reducing waiting lists.

This will be achieved through the following objectives:

1. Acquire data and expert-based evidence and optimise data augmentation to ensure optimal hospital patient pathways through pre-operative assessment, surgery, anaesthetic normal recovery, extended recovery, and ICU services: bookings, utilisation, pre-operative and on-the-day cancellations, emergencies, and, non-attendances.
2. Establish a clinical scoring system to predict patients\’ post-operative anaesthetic recovery needs to three severity and associated care levels and respective predicted nurse-to-patient ratio required (complexity).
3. Develop and optimise a modelling pipeline including a decision support dashboard for optimal patient selection for surgery to ensure daily surgery caseload optimisation, post-operative care manageability, patient safety, and reduce waiting lists.

You will need to demonstrate you:

• meet the academic requirements for a PhD offer from the University of Reading
• have a MSc degree in Computer Science or a related discipline
• are able to effectively organise your time and prioritise tasks to balance PhD studies with GTA responsibilities
• are able to demonstrate scholarship in developing a publication record in your area of specialist expertise and conduct high quality PhD research
• are able to communicate scientific concepts clearly and with enthusiasm and in a way that engages students
• Have good interpersonal skills and be able to work as part of a team

See candidate pack at the bottom of the page for further details.

Candidates will be provided with training to develop teaching and pedagogical skills, no prior experience of teaching is necessary. On the research side, our package of support includes access to MSc courses and bespoke training through our Postgraduate and Researcher College will help you in developing your professional skills as a researcher.

Working hours for the teaching portion will be variable during the academic year but will be no more than 20 hours per week. The terms of the offer of funding for the PhD and the offer of employment will rely upon the postholder being registered as a full-time doctoral student.

Successful candidates will be paid an annual salary (£8745) and stipend (£15585 per annum) over the 4 year period and will have PhD fees waived at the Home level (Please note that students liable for international fees will need to pay the difference between these and the home fee rate). Fees for 2025/26 (amount payable each year) can be found here .

How do I apply?

You must upload a combined CV and Proposal in pdf format (max size 1 MB) and complete the supporting statement.

We look forward to hearing from you!
Contact details for advert

Contact Name Dr Ferran Espuny-Pujol

Contact Job Title Lecturer in Computer Science

Contact Email address f.espuny-pujol@reading.ac.uk

The University is committed to having a diverse and inclusive workforce, supports the gender equality Athena SWAN Charter and the Race Equality Charter, and champions LGBT+ equality. We are a Disability Confident Employer (Level 2). Applications for job-share, part-time and flexible working arrangements are welcomed and will be considered in line with business needs. #J-18808-Ljbffr