Marie Curie Early Stage Researcher (Computational)

University College London (UCL) is a globally recognised university with a strong reputation for academic excellence, innovation, and real-world impact. UCL Mechanical Engineering conducts high-quality research across healthcare technologies, sustainable fuels, green energy, and advanced manufacturing. In the Research Excellence Framework (REF 2014), over 90% of the department’s research was rated world-leading or internationally excellent. Doctoral researchers benefit from access to advanced laboratories, high-performance computing, and a well-established research training environment within a leading UK institution.

This position forms part of ThromboRisk, an EU-funded Marie Skłodowska-Curie Doctoral Network that brings together ten European institutions, including UCL, to develop multi-level models for thrombosis risk prediction. ThromboRisk integrates mechanobiology, biochemistry, pathophysiology, and computational modelling to improve understanding of thrombus formation, growth, rupture, and clinical impact. The network will recruit 18 Doctoral Candidates who will work within a strongly interdisciplinary and international programme, supported by structured scientific and professional training, Challenge-Based Learning, and close collaboration across the consortium.

The role is hosted within UCL’s Hawkes Institute, which focuses on translating innovative healthcare technologies into clinical solutions addressing significant medical challenges.

This 36-month doctoral position offers an opportunity to conduct research on patient-specific thrombosis in Type-B aortic dissection using computational and simulation-based approaches, including Computational Fluid Dynamics and/or physics-informed AI tools. Thrombosis in the false lumen can influence disease progression and patient outcomes, with both stabilising effects and potential complications. The project will focus on developing predictive in silico models of thrombosis in the false lumen and examining correlations between haemodynamic markers and thrombotic outcomes using data from a small patient cohort provided by a European partner hospital. The research topic will be refined collaboratively with the Doctoral Candidate using Challenge-Based Learning principles.

The project will be based at UCL under the supervision of Professor Vanessa Diaz and Professor Stavroula Balabani. Doctoral training will include secondments of three to six months at partner institutions in Europe, providing international research experience and exposure to complementary expertise. The successful candidate will be enrolled as a doctoral student in UCL Mechanical Engineering and awarded a PhD from University College London in Computational Biomechanics or a closely related discipline.

Applicants should hold a UK-equivalent first-class Master’s degree in a relevant discipline and be within four years of full-time equivalent research experience, without holding a doctoral degree. Essential skills include strong knowledge of fluid mechanics, experience in computational flow modelling, programming skills, effective written and verbal communication, and the ability to work collaboratively in a multicultural research environment.

In line with Marie Skłodowska-Curie mobility requirements, applicants must not have lived or worked in the UK for more than 12 months in the three years prior to recruitment. Total annual remuneration ranges from £36,530 to £47,630, depending on eligibility. UCL offers a wide range of staff benefits; further details are available via the UCL Rewards and Benefits webpages.

As London’s Global University, UCL is committed to equality, diversity and inclusion, and actively encourages applications from candidates underrepresented in its workforce. UCL Mechanical Engineering holds an Athena SWAN Bronze award in recognition of its commitment to advancing gender equality.

International applicants motivated to pursue doctoral research within a structured European Marie Skłodowska-Curie network are encouraged to apply by following the APPLY button and submitting a supporting statement demonstrating how they meet the selection criteria.

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