Research Associate: Digital Twinning and In Silico Trials (Medical Devices)

Location: Manchester, Greater Manchester, United Kingdom. Conditions: Oxford Road.

Salary: £37,694–£46,049 per annum depending on experience.

Company

hirify.global contributes to Federated Data Science UK, a national consortium developing a federated network of secure health-data environments.

What you will do

• Lead the scientific delivery of an in silico medical-device trials use case, scaling the FD-PASS intracranial aneurysm cohort more than a hundred-fold using digital twins and federated imaging and electronic health record data.
• Develop automated, efficient, and reproducible image-based modelling and simulation workflows for cardiovascular and cerebrovascular systems, with and without implanted devices.
• Define use cases, technical specifications, data and compute requirements, interoperability needs, and provenance tooling requirements for national federated research infrastructure.
• Design evaluation and benchmarking frameworks covering model credibility, verification, validation, uncertainty quantification, device safety, efficacy, and failure modes.
• Develop generative and statistical anatomical models, deep-learning flow-field models, and person-specific physiological boundary conditions for virtual populations.
• Communicate complex technical information to clinical, regulatory, public, and scientific audiences in writing and in person.

Requirements

• PhD or equivalent research experience in computational cardiovascular and/or cerebrovascular modelling, biomechanics, medical image analysis, or a closely related field.
• Domain expertise in digital twinning and in silico trials, including computational modelling and simulation for medical-device design, evaluation, and regulatory assessment and construction of virtual-patient cohorts.
• Advanced proficiency in finite element analysis and/or computational fluid dynamics for cardiovascular applications.
• In-depth experience with commercial and open-source simulation software for in silico trials and cardiovascular research, such as ANSYS CFX or Fluent, COMSOL, OpenFOAM, or FEniCS.
• Strong Python software-development skills for efficient computational-science and engineering algorithms, with familiarity with C/C++ or MATLAB.
• Excellent communication skills for explaining complex technical information to varied audiences.

Culture & Benefits

• Generous employer pension contribution.
• 29 days of annual leave plus bank holidays and Christmas closure.
• Ride-to-work and EV car schemes available.
• Open environment focused on enquiry, challenge, diversity, debate, education, learning, and community.
• Flexible and hybrid working information is provided by the university.

Hiring process

• Applications close at midnight on the closing date.
• Role enquiries, shortlisting, and interview enquiries can be directed to Professor Alejandro Frangi.