The Regenerative Medical Engineering (RME) Cluster of Biomedical Engineering would like to welcome a new faculty member to run a line of research and education to complement ongoing topics at the cluster Regenerative Medical Engineering. The mission statement of the RME cluster is to impact science and society by developing innovative bioengineering solutions and enabling technologies through collaborative research excellence and by educating the professionals of the future.
The Department of Biomedical EngineeringResearch at the department of Biomedical Engineering is aimed at training the next generation of biomedical engineers that combine engineering skills with a strong background in the natural and life sciences to address biomedical challenges. We aim for scientific excellence through an engineering approach, where engineering is defined both as an enabler of scientific and societal progress and as a scientific method to acquire scientific knowledge (learning by making). The combination of engineering and life sciences positions us well to make significant contributions to several exciting and promising research areas including immune-engineering and regenerative medicine, systems and synthetic biology, the application of AI in molecular design, image analysis and medical decision support. The scientific questions we address are inspired by fundamental challenges in biomedicine and healthcare and we actively pursue the translation of scientific insights and new therapeutic and diagnostic approaches in partnership with hospitals and other healthcare providers and medical industry, and by promoting biotech entrepreneurship among our staff.
The Cluster Regenerative Medical Engineering (RME)The RME cluster aims to create solutions for biomedical and clinical problems by applying an engineering approach in the field of regenerative medicine. The cluster's research includes basic and applied research as well as methodological innovations in the field of biomaterial and tissue engineering, computational modelling and advanced cell screening. The research has a strong focus on cardiovascular, orthopaedic and connective tissue as well as mechanobiology. The research groups in this cluster are internationally highly competitive in the field of regenerative medicine.
The current 15 faculty staff members of the cluster cover a range of research areas, including bone, cartilage, disc and tendon engineering, blood vessel and heart valve engineering. More specifically, the group is known for its
work in high throughput screening and engineered living tissues. Other strong lines are on finite element model of tissue structure, function and formation, immuno-engineering of cellular and tissue responses and biofabrication. Research is performed in direct collaboration with
clinical partners.
The educational curriculum of the cluster includes all relevant basic and applied courses in the fields of tissue engineering and regenerative medicine at the Bachelor and Master level with a keen eye for frontier engineering approaches. Moreover, the Department is running a
joint master track in Regenerative Medicine and Technology together with University Medical Center Utrecht.
Collaborations and opportunitiesThe RM field in the Netherlands is extensive and internationally leading. The RME cluster at TU/e is positioned well within the Dutch landscape, with good connections
to the other groups. Members of the group are involved in the
Materials Technology Institute, the
Institute for Complex Molecular Systems and
EAISI, TU/e's cross-departmental institute for Artificial Intelligence. RME staff take leading positions in several national and international RM consortia, and many have obtained prestigious grants such as ERC Starting and Advanced grants. RME staff are expected to supervise PhD students based on externally acquired funding.
In the
Department of Biomedical Engineering, RM is a topic of common interest across
research groups, as for instance in biomaterial engineering and computational modelling. Within TU/e,
collaborations exist with the Department of Mechanical Engineering, on for example lab-on-chip development,
and with the Department of Mathematics and Computer Science, on methodological advancements
of AI.