We are looking for a motivated and independent PhD candidate to develop highly efficient and robust surrogate models of a multi-scale cardiovascular ‘digital twin’ modelling platform.

A cardiovascular digital twin is a physics-based computer simulation that models an individual’s health and disease states to aid decision-making. These high-fidelity models are often computationally expensive, limiting their personalization and real-time clinical use. In this project, we aim to develop highly efficient data-driven surrogate models for parametrized partial differential equations, with application to computational cardiology.

In this project, you will combine advanced physics-based models of the human heart and vasculature with the latest breakthroughs in machine learning to develop scalable and robust surrogate models of cardiovascular digital twins. These surrogate models will be used to enhance personalized treatment planning and post-treatment monitoring for patients suffering from circulation overload disorders, specifically systemic hypertension, heart failure (with/without preserved ejection fraction), and hemodynamically complicated atrial septal defects.

The research will be conducted in the Department of BioMechanical Engineering at Delft University of Technology (TU Delft) under the supervision of dr. ir. Mathias Peirlinck. The Peirlinck Lab integrates multimodal experimental data, physics-based modeling, and machine learning techniques to understand, explore, and predict the multiscale behavior of the human heart and cardiovascular system. More information on the research and team can be found on https://peirlincklab.com. This research is part of the VITAL project (https://vital-horizoneurope.eu/), a large international collaboration developing a comprehensive, clinically validated, multi-scale, multi-organ ‘digital twin’ modelling platform that is driven by and can represent individual patient data acquired both in the clinic and from wearable technology.

Prior experience in both scientific machine learning and numerical analysis of PDEs and ODEs is required. In addition, experience in the field of cardiac modeling, arterial modeling, (soft tissue) biomechanics, and/or electrophysiology will be strongly appreciated. As the successful candidate for this position, you will develop scientific machine learning algorithms, develop and run high-performance computer simulations, construct pipelines for model personalization to structural and functional data, and develop APIs between various software codes. You will actively participate in (bi)weekly lab meetings, write scientific articles and reports, and give presentations and workshops at national and international conferences. Besides your research activities, you will also take part in teaching and supervision activities within the Faculty of Mechanical Engineering of Delft University of Technology and beyond.

More information:

https://www.tudelft.nl/over-tu-delft/werken-bij-tu-delft/vacatures/details?jobId=17669

REBONE is a four-year Doctoral Network, funded by the Europe Horizon Marie Skłodowska programme, aiming at innovatively training a new generation of researchers to develop a multidisciplinary optimization process aimed at providing technologies for personalized bone-substitute implants, based on bioactive ceramics to address the health and societal burdens of trauma and bone diseases.

The musculoskeletal system is extremely vulnerable to ageing and traumatic events, and common clinical conditions often impose a high burden on the clinical system. For patients requiring bone-substitute implants to treat critical-size bone defects, new solutions are needed to address important unmet needs: personalised solutions for better clinical outcomes; improvements in materials to ensure higher mechanical reliability without compromising bioactive and bioresorbable properties; optimised manufacturing technologies for materials and products of high reliability and quality.

In order to achieve these ambitious goals REBONE is about to open 10 fully funded PhD positions to  construct a platform of computational tools that will enable clinical experts to produce customized bone graft substitutes for the treatment of critical-size bone defects. This innovation will ensure that an ideal treatment solution is found on a patient-specific basis in terms of:

• mechanical and mechano-biological performance,
• surgical implantability, and
• manufacturing process reliability.

Furthermore, REBONE will develop state-of-the-art in silico models based on advanced computational methods and advanced characterisation and validation techniques to obtain personalised implants with a surgical planning visualization system in mixed reality with the following characteristics:

• tailored and reliable mechanical and physical properties;
• best osteointegration capability;
• targeted mechanical, physical and mechano-biological functions with patient-specific constraints taking into account the load-bearing anatomical location. Four selected clinical cases will be used as demonstrators of the optimization design and manufacturing processes.

LIST OF AVAILABLE PhD POSITIONS

Complete list of the 10 Doctoral positions available within REBONE:

1. Position 1: Methods for optimization of bone-substitute architectures (Politecnico di Milano, Italy);
2. Position 2: Micro- and macro-mechanical characterization of materials and devices and in-silico Models (Politecnico di Milano, Italy);
3. Position 3: 3D printing technologies for Glass-Ceramic and Glass-Ceramic-based composite BTE scaffolds (Politecnico di Torino, Italy);
4. Position 4: Tissue-scaffold biological interaction (Università del Piemonte Orientale, Italy)
5. Position 5: Design of bone inspired scaffolds and biomechanical characterization of the bone-scaffold construct (Université de Liege, Belgium)
6. Position 6: Industrial process for glass-ceramic device manufacturing through VPP (Lithoz GmbH, Austria)
7. Position 7: Characterization of fracture relevant bone sites for information on the structural/compositional requirements of the implant (Ludwig Boltzmann Institute, Austria)
8. Position 8: Models for Tissue growth and fundamental relationships with micro-architecture of scaffolds (University of Salzburg, Austria)
9. Position 9: Biomimetic in vitro culture models for evaluation of novel bone substitute implants (University of Belgrade, RS)
10. Position 10: Mixed reality for planning of implant surgery for bone defects of irregular shapes (MEDAPP SPÓŁKA AKCYJNA, Poland)

For info and application procedure please visit the project website https://rebone.eu/ and here: