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PhD Position Scientific Machine Learning and Surrogate Modeling for Cardiovascular Digital Twins @TU Delft

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 This research is part of the VITAL project (, 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:

Join the VMHTsOP project!

Four Research positions available at Insigneo (University of Sheffield) to join the “Virtual Mouse and Human Twins for optimising Treatments for Osteoporosis (VMHTsOP)” project!
The VMHTsOP project aims at developing the first inter-species Virtual Mouse-Human Twin for predicting bone adaptation over time and optimise biomechanical and/or pharmacological treatments for Osteoporosis. It is a 5 years project that will start in September 2024, led by Prof Enrico Dall’Ara at the University of Sheffield, Division of Clinical Medicine and Insigneo institute. The project has been selected by ERC-consolidator grant and funded by the EPSRC through the EU Guarantee fund.
Don’t miss the opportunity to join the team for this exciting research project!

Current Available Positions:
Research Associate (PostDoc) in “Preclinical musculoskeletal imaging and biomechanics”; 3yrs; start in Sep 2024; closing date applications 4th June 2024
Research Associate (PostDoc) in “Computational musculoskeletal biomechanics”; 3yrs; start in Sep 2024; closing date applications 4th June 2024
Research Technician with expertise in imaging and histology; 3yrs; start in Sep 2024; closing date applications 4th June 2024
PhD student in “A biochemo-mechano multi-scale computational model to predict bone adaptation over space and time”; salary and fees (for UK students) for 3.5yrs; start in Oct 2024; closing date applications 10th June 2024
For any enquiries, please contact Prof Enrico Dall’Ara at

Summary of the project
Eighty per cent of pharmaceutical interventions fail in patients even after being successful in animal studies. Musculoskeletal (MSK) diseases such as osteoporosis (OP) reduce dramatically the quality of life of millions of affected patients. Mice are the most common animal model to test new treatments. Nevertheless, the extrapolation of their effect onto patients and the identification of which new treatments should be tested in clinical studies is based on simple scaling approaches.
In this project we will develop a new mechanistic computational framework that bridges between mouse and human, informed by in vivo experiments in mice, to discover optimal treatments in patients. We will create two parallel virtual mouse and human twins (VMHTs-OP), based on similar inputs (biomedical images, cell data, gait data) that will predict bone adaptation in function of biomechanical and/or biochemical stimuli. Each virtual twin will be based on advanced multi-scale computational models (multi-body dynamics, finite element and cell-population models) to predict bone adaptation over time and space due to OP and to new biomechanical and pharmacological treatments, identifying in silico the new combined treatments that are likely to be effective in patients, to be tested in future clinical trials.
The models will be going through a comprehensive verification, validation and uncertainties quantification process in order to provide the required credibility for future preclinical applications. The model predictions will be validated against longitudinal mouse experiments and available longitudinal clinical data from known biomechanical or pharmacological interventions. Finally, the validated framework will be used to test in silico several combinations of treatments regimens (overlap, intermitted, drug holidays) and different interventions (microgravity, high strain exercises) that would not be ethically nor economically testable in animal and clinical trials.

4 positions at the Institute of Medical and Biological Engineering (IMBE) in Leeds, UK

The Institiute of Medical and Biological Engineering (IMBE) in Leeds, UK, is currently recruiting for 4 positions:

  1. researcher (research fellow requiring a PhD or research assistant requiring a Master) in computational damage biomechanics: (for the research assistant role, check your UK working eligibility by contacting
  2. post-doctoral research (research fellow requiring a PhD) in knee and hip biomechanical evaluation:
  3. PhD student in spine biomechanics:
  4. PhD student in bone healing:

All details of application processes are available on the respective links, deadlines within the next month.

The multi-disciplinary IMBE is embedded within the School of Mechanical Engineering and the Faculty of Biological Sciences at the University of Leeds. It is a dynamic world-renowned medical engineering research centre which specialises in research and translation of musculoskeletal and cardiovascular medical technologies that promote ’50 active years after 50’.

As a researcher or PhD student within IMBE, there will be opportunities to contribute to wider activities related to medical technologies including public and patient engagement, group training and social events. Groups of researchers working on aligned projects or using similar methods meet regularly to share ideas and best practice, and we encourage collegiate working. We will support your long-term career ambitions through bespoke training and encourage external secondments, laboratory visits or participation at international conferences.

10 PhD positions in the Europe Horizon Marie Skłodowska-Curie Project REBONE

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.


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 and here:

2 PhD positions on atherosclerotic arterial wall biomechanics @Erasmus MC & TU Delft

The Cardiovascular Biomechanics Group at Erasmus Medical Center / TU Delft has two PhD positions available currently, both on atherosclerotic arterial wall biomechanics, one experimental and the other one computational.

Further info can be reached at

Application for the openings:

Position 1.)

Position 2.)

2 PhD positions in cancer mechanobiology @University of Galway

Applications are invited from suitably qualified candidates for multiple full-time, fully-funded positions that will investigate the mechanobiology of tumour growth and therapy resistance. These positions are funded by a European Research Council Starting Grant and will be under the supervision of Dr Eoin McEvoy, Assistant Professor in Biomedical Engineering. The researcher will join Dr McEvoy’s group, which brings together expertise in biophysical modelling, active cell biomechanics, and in-vitro tumour models. The group’s overall focus is to develop advanced computational and experimental models that provide a mechanistic understanding of cell and tissue remodelling in cancer and disease, motivating novel mechano-therapeutics and treatment strategies. For further information, see

Project Description: Personalised medicine presents an exciting frontier in healthcare that tailors disease mitigation and intervention to an individual patient. This project will develop integrated experimental and computational models for the prediction of cancer patient outcomes, leveraging the biophysical forces that underpin cell behaviour. PhD research topics will bridge subcellular remodelling, single cell mechanobiology, and macroscale tumour evolution to provide a new and fundamental understanding of tumour growth and therapy resistance in breast cancer. As part of the PhD programme (project dependent), you will receive training in computational and experimental cell mechanics, patient-derived tumour organoid generation, microfluidic cell culture, advanced microscopy, agent-based modelling, and/or advanced finite element analysis.

Application Deadline: Applications will be reviewed periodically until January 31st, 2024.

More information:

PhD position – FE modeling of breast compression during mamography @Lund University

We have an open PhD position at Lund University, Sweden, with focus on developing FE based simulation models for breast compression during mamography with implications for breast cancer diagnostics. Please see the link below for more information!

PhD position in computational cardiovascular mechanics @University of Glasgow

I am looking for motivated students to join my research group and work towards their PhD in the area of computational cardiovascular biomechanics. Interested candidates are encouraged to email to discuss further. More details of the PhD position are provided below.

Project Summary: Almost 30% of all deaths globally are related to cardiovascular diseases. The overall aim of computational cardiovascular biomechanics is to help improve the diagnosis of these diseases (faster, earlier, more precise), provide better surgical outcomes, and design devices that last longer. To achieve that aim, we study the biomechanical properties of tissues and cells comprising the cardiovascular system using a combination of in-vivo imaging, ex-vivo and in-vitro testing, and in-silico modeling. Several project topics are available, which can be categorized into model development (at organ and cellular scales) and method development (based on imaging and using data science approaches). A few examples of specific projects are:

1) Predicting aneurysm development from ultrasound images using growth and remodeling simulations
2) Modeling of endothelial cells based on in-vitro experiments
3) Uncertainty quantification of biomechanical properties based on combined ex-vivo and in-vivo dataset
4) Gaussian process modeling for cardiovascular tissue mechanics
5) Development of a digital twin of the thoracic aorta

During this project, the student will have opportunities to:

  • Develop skills necessary to work at the interface of engineering and biomedical science
  • Publish papers in high-quality journals
  • Present research results at international conferences
  • Learn about nonlinear finite element analysis, nonlinear mechanics, multiscale modeling, image-based analysis, data science, and other numerical techniques
  • Learn about experimental and clinical validation
  • Collaborate with our international academic and industrial partners
  • Interact within the Glasgow Centre for Computational Engineering with other researchers (GCEC) and across departments with biomedical scientists and clinicians

Eligibility: Candidates must have an undergraduate degree in a relevant field, such as Mechanical Engineering, Biomedical Engineering, Civil Engineering, Mathematics and Computing Science, with a minimum 2.1 or equivalent final grade. A background in mechanics and knowledge of numerical methods (such as finite element analysis) would be necessary. Programming skills will be required for computational modeling.

Application: The deadline for applications is 31 January 2024, and the application process consists of two parts:
1) On-line academic application: Go to and click on the ‘Apply now’ tab. Applicants should attach relevant documents such as CV, transcripts, references and a research proposal.
2) School of Engineering EPSRC/School Scholarship Application via online portal:] To complete the scholarship application, students will need a supporting statement from the proposed supervisor. Any queries about application procedure can be directed to

Further information: If you are interested or want more information, please contact me at my email ( before starting the formal application. Please visit Computational Biomechanics Research Group page or my staff page for more information on our research.

PhD Studentship in Data-driven image mechanics (D2IM): a deep learning approach to predict displacement and strain fields in biological tissues from X-ray tomography @University of Greenwich

The recent advent of deep learning (DL) has enabled data-driven models, paving the way for the full exploitation of rich image datasets from which physics can be learnt. Here at the University of Greenwich we recently developed a novel data-driven image mechanics (D2IM) approach that learns from digital volume correlation (DVC) displacement fields of bone, predicting displacement and strain fields for undeformed X-ray computed tomography (XCT) images [1]. This was the first study using experimental full-field measurements on bone structures from DVC to inform DL-based model such as D2IM, which represents a major contribution in the prediction of displacement and strain fields only based on the greyscale content of undeformed XCT images. The proposed PhD project will expand on this work to further develop D2IM capability by incorporating a range of biological structures (hard and soft tissues) and loading scenarios for accurate prediction of physical fields.

The project will benefit from a unique InCiTe 3D X-ray microscope from our partner KA Imaging ( capable of sub-micron resolution and fast phase-contrast (first and only technology of this type in Europe), including in situ mechanics and dedicated software solutions available at the Centre for Advanced Materials and Manufacturing (CAMM) as well as the Centre for Advanced Simulation and Modelling (CASM).

The PhD candidate will be involved in the following work:

  1. Development of XCT protocols on the InCiTe 3D X-ray microscope including phase retrieval for in situ mechanics and DVC of hard and soft tissues.
  2. Development of novel DL strategies to enhance D2IM capability for a comprehensive prediction of displacement and strain fields in biological tissues, only based on the greyscale content of undeformed XCT images.
  3. Data analysis and dissemination. Data obtained from this project will be disseminated in high-impact journal papers and international conferences.

[1] Soar and Tozzi, 2023. Data-driven image mechanics (D2IM): a deep learning approach to predict displacement and strain fields from undeformed X-ray tomography images – Evaluation of bone mechanics.

More information:

PhD position in Computer mechanobiology of mandibular reconstruction @Charité -Universitätsmedizin Berlin

A PhD position is available within the Computational Mechanobiology Group at the Julius Wolff Institute (Charité – Universitätsmedizin Berlin), led by Prof. Sara Checa. This position is funded through a research grant from the German Research Foundation (DFG) to investigate the biomechanics of mandibular reconstruction with fibular free flap.

The successful candidate will have a strong background in one or more of the following areas: mechanics, computational biology and/or computational mechanics. Strong programming and computer modelling skills are required. The position is available for two years with an option to renew provided that adequate progress is made.

The work will be conducted in an interdisciplinary research environment composed of engineers, biologists and clinicians. As a PhD student, you will be associated to the Berlin-Brandenburg School of Regenerative Therapies ( and benefit from the interaction with international scientists.

The position will remain open until the position is filled. Applications should be sent to: Prof. Sara Checa (

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