We currently have 5 vacancies in the School of Engineering and Materials Science:
Postdoctoral Research Associate
Salary: £39463 - £44,811 per annum
Reference: 6618
Location: QM London
Closing date: 8 August 2025
Queen Mary University of London has a Postdoctoral Research Assistant vacancy to join the multidisciplinary project entitled “Human Tendon-CHIP: Novel In Vitro Predictive Models to Explore Tendinopathy”. The project is funded by the Medical Research Council (MRC) and part of the organ-chip research work underway within the Centre for Predictive in Vitro Models.The project aims to use organ-on-a-chip technology combined with bioengineering approaches to develop, validate and use a suite of vascularised human tendon-chip models. These high quality physiologically relevant models will provide crucial platforms to mimic disease pathology, and better understand and treat tendinopathy. The project will generate tendon-chips using in-house commercially available platforms at our prestigious Centre for in vitro Predictive Models (
https://www.cpm.qmul.ac.uk/), and work with project partners based at the Cross Institute Advanced Tissue Engineering (CREATE) lab at the Blizard Institute to build and test custom made tendon-chips, using advanced bio fabrication techniques. You will join the Screen research group - a multidisciplinary team of scientists from engineering and biomedical sciences backgrounds combining expertise in organ-chip technology, cell biology, bioengineering and bio fabrication, with a collective aim to better understand tendon physiology and disease.
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PDRA in Dielectric Elastomer Actuator Devices and Sensors
Salary: £23,413.20 (pro rata - 60% to £ 39,022 per annum)
Reference: 6907
Location: QM London
Closing date: 14 August 2025
We are looking for a motivated Postdoctoral Research Associate (PDRA) to join the Soft Matter Group (SMG), led by Prof James Busfield. You will be a key member of the SMG, contributing to our development and the success of our mission.The core responsibility of this role is the further development of different dielectric elastomer actuator devices and optical sensors. This includes prototype soft elastomer actuated lenses and mechano-chromic pressure sensors. This project will help the PI (James Busfield) to write up these discoveries as high impact journal papers. You will contribute to the success of the research project through close collaboration with project partners and members of the SMG.The role is part-time, fixed term based - funded for 6 months in the first instance, with an expected start date as soon as possible.
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Senior Mechanical Workshop Technician
Salary: £43,677 - £51,040 per annum
Reference: 6858
Location: QM London
Closing date: 14 August 2025
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Research Lab Technician (Bioengineering)
Salary: £39,463 - £45,974 per annum
Reference: 6883
Location: QM London
Closing date: 21 August 2025
Further Details and Apply »
Postdoctoral Research Associate in Twins
Salary: £38,419- £51,755 per annum
Reference: 6746
Location: QM London
Closing date: 1 September 2025
The combination of personalised biophysical models and deep learning techniques with a digital twin approach has the potential to generate new treatments for cardiac diseases. Our research aims to optimise personalised treatment approaches for atrial fibrillation patients by using long-term therapy outcomes across populations of patients to inform patient-specific predictive treatments. To achieve this, we will develop personalised cardiac models at scale, and update these models over time, using imaging and electrical data collected by collaborators at multiple centres. We are seeking to appoint a postdoctoral research associate as part of a UKRI Future Leader Fellowship funded research programme.The successful candidate will work as part of a team to develop and apply deep learning approaches to predict long-term treatment outcome from imaging and electrical data on clinical timescales, using a virtual cohort as additional training data. The candidate will also develop novel techniques to update digital twin models over time using longitudinal data, to improve long-term treatment prediction. Finally, the candidate will work with members of our Personalised Cardiac Modelling lab (pcmlab.co.uk) to develop a prototype tool for utilizing this prediction tool in a clinical environment.
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