ESBiomech23 Congress in Maastricht

Postdoc position in data-driven modelling for endovascular thrombectomy @CIMNE Barcelona

We are looking for a postdoctoral researcher to work on the project MECA-ICTUS, a 3-year project funded under the Generación de Conocimiento 2022 call of Agencia Estatal de Investigación. In MECA-ICTUS we will pursue the development of computational mechanics and machine learning tools for predicting the success of endovascular thrombectomy, an urgent intervention for the removal of thrombi in Acute Ischemic Stroke Patients.

The selected candidate will be responsible of 1) development of computational mechanics tools within an on-going Finite Element framework in Julia language, in which the PI and collaborators have worked during the last 4 years, and 2) development of machine learning models to predict the success of the intervention.

The project is meant to ensure the professional growth of the selected candidate. He/she will work in CIMNE/LaCàN (UPC), an enriching environment with a strong expertise in computational mechanics, biomechanics and data-driven modelling. The project will also involve exchanges with international researchers in France, Italy and USA as well as continuous exchanges with clinicians to ensure the adequacy of the numerical developments.

For applications, please see details below.

For any enquiries don’t hesitate to reach the project PI, Miquel Aguirre ( No application will be accepted by e-mail.

 Required skills:

  • A PhD in applied mathematics or engineering in the field of computational mechanics.
  • Strong knowledge of nonlinear continuum mechanics.
  • Programming experience in scientific computing.
  • Experience in the development of finite element software.
  • Writing and communication skills.

Other valued skills (not mandatory):

  • Experience in the development of machine learning models.
  • Experience in Julia programming.
  • Experience in the development of nonlinear solid mechanics solvers, involving large deformations and/or contact and/or fracture.
  • Experience in preprocessing medical imaging data for patient-specific simulations.

Qualification system:

The requisites and merits will be evaluated with a maximum note of 100 points. Such maximal note will be obtained summing up the following points:

  • Publication and career track: 10%
  • Previous research and/or academic experience in the field of the position: 20%
  • Programming skills: 20%
  • Language and communication skills: 20%
  • Interview: 30%

Candidates must complete the “Application Form” form on our website, indicating the reference of the vacancy and attaching the required documents.

The deadline for registration to the offer ends on September 30, 2023 at 12 noon.

The preselected candidates may be requested to send the documentation required in the “Requirements” and “Merits” sections, duly scanned, and may be called to go through selection tests (which might be of eliminatory nature) and / or personal interviews.

Proyecto PID2022-136668OA-I00 financiado por MCIN/AEI/10.13039/501100011033/ FEDER, UE

Further details and application link:

Two open post-doctoral positions @Lund University

We have two open post-doctoral positions in our team – one experimental related to image analsyis of soft knee tissues, and one numerical related to computational modeling of tendon mechanics. 

1: Experimental synchrotron imaging of soft knee tissues:

We are looking for a post-doctoral researcher focusing on synchrotron imaging and image analysis to join our team.  The goal for the post-doc is to develop, perform and primarily analyze data from high resolution experimental imaging of soft tissues, acquired mainly using synchrotron phase contrast X-ray tomography, but also other imaging modalities. The goal includes characterizing meniscus and cartilage microstructure and its relation to loading, based on in situ loading experiments during imaging.

The link to the full advertisement and application system is below:

Application deadline:  6th of July

Please contact Prof. Hanna Isaksson ( with any questions.

2: Numerical modeling of achilles tendon mechanics and/or mechanobiology:

We are looking for a post-doctoral researcher in computational modeling of tendons. This position is within a larger ERC-funded project (Tendon_MechBio) with the scope to elucidate how mechanical loading affects tendon mechanics and tendon regeneration. There is a possibility to employ up to two postdoctoral researchers with the following two aims. 

  1. To investigate how mechanical loading influences healing tendon function, structure and composition. The project includes further developing and validating an existing adaptive mechanoregulatory model for tendon repair. This will be based on collected experimental data. The developed computational scheme will be important for the project to elucidate the mechanobiological mechanisms at play. 
  2. To develop detailed structural and anatomical computational models of the tendon tissue, in order to understand how mechanical loading influences tendon function, structure and composition. The computational modeling will be based on unique collected experimental data. The detailed structural models will be key in the project to elucidate the mechanisms guiding the tendon organ and tissue level response to load. 

Applicants can present preferences between aim 1 or 2, or state interest in both options.

The link to the full advertisement and application system is below:

Application deadline: 6th of July

Please contact Prof. Hanna Isaksson ( with any questions.

Postdoc position on Computational modeling of drug-toxin interactions in the kidney @Maastricht University

The department of Cell Biology-Inspired Tissue Engineering (cBITE) at the MERLN Institute for Technologyinspired Regenerative Medicine at Maastricht University in the Netherlands invites applications for a postdoctoral position. The post-doctoral researcher will perform cutting-edge research in computational modeling methods applied to drug-toxin interactions in the kidney. Chronic kidney disease (CKD) is one of the top ten causes of death worldwide. Gradual decline in kidney function leads to accumulation of metabolic waste products (toxins) normally excreted by the kidneys, contributing to progression of CKD and its comorbidities, in particular cardiovascular disease. To alleviate the CKD complications, patients are routinely treated with many drugs, such as antihypertensive and cholesterol-lowering agents. However, the transporter proteins in kidney cells that handle these drugs are also responsible for secreting the toxins, and may, therefore, not be able to handle the competing demands. Considering the multitude of CKD drugs, toxins and transporter proteins and their potential interactions, investigating drug-toxin interactions is experimentally time consuming and difficult to accomplish. In this project, funded by the Dutch Kidney Foundation (, we propose to integrate computational and experimental expertise with state-of-the-art technologies to address investigate drug-toxin interactions in the kidney and improve CKD drug treatments.

Project description: 

  • Computational modeling of drug-toxin transport in the proximal tubule; (competitive) binding kinetics;
  • Sensitivity analysis;
  • Analysis and integration of various in vitro/in vivo data for model calibration;
  • Parameter optimization.

Application deadline: 29 June 2023

More information:

2 positions on imaging and biomechanics in spine surgery planning @SKAIROS

SKAIROS is a deeptech startup which aim is to translate subject specific finite element spine models to the real life, to help for spinal implants design and surgery planning.

More information on the two job descriptions:

Senior postdoctoral researcher data science & machine learning @Universitat Pompeu Fabra

Research Project

O-Health is a Consolidator grant from the European Research Council, awarded by the European Commission under the HORIZON Action. It is led by Prof. Jérôme Noailly, from the BCN MedTech research unit of the Department of Information and Communication Technologies (DTIC), at the Universitat Pompeu Fabra (UPF), Barcelona, Spain.

Non-communicable diseases (NCD) that involve load-bearing organs emerge silently according to complex mechanisms that are likely to involve inter-disease systemic communications. Clinical explorations cannot apprehend such intricate emergence, O-Health postulates that multiscale in silico models can. Digital twin technologies for health have progressed a lot in the last decades, but multi-disease transversal modelling at the body scale is yet to be developed. It requires to couple small to large-scale model components with appropriate balance of phenomenological and mechanistic approaches, to cope with overwhelming biological complexity, preserve interpretability and incorporate real-world data. This is the niche of O-Health that proposes a scalable ecosystem of multiscale NCD models interrelated through a body-wide systemic model of low-grade inflammation. The project tackles such vertical and transversal physiology-based computational modelling through four major NCD, lung emphysema, atherosclerosis, intervertebral disc degeneration and knee osteoarthritis that affect load-bearing organs at different anatomical locations. Each NCD model will vertically share predicted variables with an interface model of endothelial cell dysfunction that communicates with a transversal model of body-wide systemic communications. The O-health ecosystem shall be modular and interoperable. Models and simulations will combine finite element models at the organ /tissue scales and systems biology models at lower scales, with machine learning models for the incorporation of real-world data out of population cohorts. Interoperability shall be ensured through declarative standard languages such as Field and Systems Biology Mark-up Languages.

Description of the position

The successful Candidate will be a senior postdoctoral researcher, with proven experience in data science and machine learning. He/She will be based at DTIC, UPF and will be responsible for the management and mining of health data collected for the O-Health project, out of existing patient and population cohorts. Scientific and technical competencies are necessary in interpretable machine learning, nonlinear unsupervised learning, as well as in federated and transfer learning. Advanced programming skills and experience in handling health and/or biomedical data are required. Knowledge of data management plans will be valued. The Researcher will become progressively responsible for the data science operations of the BMMB, to properly mine real-world health data and couple the latter to the physics- and biology-based models, developed by the other researchers of the group for interpretable predictive modelling. While a high level of independence is expected, (s)he shall report periodically to PI, to ensure (i) that the timelines of the project and deliverables are met, and (ii) that the project results can be properly disseminated through scientific and medical congresses and journals. As such, communication, teamwork, and leadership skills will be chiefly important.

More information:

Junior Postdoctoral Researcher, Machine Learning for Biomechanics @Universitat Pompeu Fabra 

BONE STRENGTH is a public-private collaboration project funded by the Spanish Ministry of Science and Innovation (MICINN) and Agency of Research (AEI) that focusses on the prediction of fragile bone fractures in osteoporosis, out of routine clinical explorations. The collaboration will take place between the technology-based company 3D Shaper Medical SL, and the Barcelona Centre for New Medical Technologies (BCN MedTech) of the Universitat Pompeu Fabra (UPF). Both 3D Shaper Medical SL and UPF are in Barcelona, Spain.

Osteoporosis is a disease associated with the occurrence of fragile fractures in the elderly population, resulting in a huge burden on the society and the healthcare system. The current clinical gold standard for fracture risk assessment is based on areal bone mineral density (aBMD) measured using dual-energy X-ray absorptiometry (DXA) scan. However, it fails to identify up to 50% of the patients eligible for bone-specific pharmacological treatments, resulting in fractures that could be prevented. Bone strength, estimated using quantitative computed tomography (QCT)-based finite element analyses (FEA), has been shown to improve osteoporosis diagnosis and management. However, increased exposure of patients to X-ray radiations is a limitation in clinical practice. 3D-Shaper Medical SL has developed a software (3D-Shaper®) validated for predicting volumetric density and geometrical parameters of the proximal femur and lumbar vertebrae from planar DXA. It can provide clinicians with QCT equivalent parameters without performing a CT scan. 

BONE STRENTH aims to develop a FEA module for 3D-Shaper® that will enable QCT-equivalent bone strength estimations from DXA scans. Through its Biomechanics and Mechanobiology Research Area (BMMB), BCN MedTech has a large experience in computational biomechanics and will develop the Finite Element methods that will be integrated into 3D-Shaper®. Bone strength calculations will be validated against experimentally measured values, and patient-specifically, against QCT-based FE predictions. Performance of the fracture risk assessment will be investigated using case-control clinical cohorts. Furthermore, the 3D-Shaper® FEA module will be used to evaluate the effect of pharmacological treatments, enabling clinical trials with a reduced economic cost and without performing CT scans.

Description of Work

BONE STRENGTH has two Principal investigators (PI). The PI at 3D Shaper Medical SL and coordinator of the project is Ludovic Humbert, Co-founder and CEO of 3D Shaper SL and expert in medical image processing and modelling in biomechanics. The PI at UPF is Jérôme Noailly, head of the BMMB at BCN MedTech, co-director of the SIMBIOSys group at the UPF Department of Information and Communication Technologies (DTIC), and expert in modelling and simulations in biomechanics and (systems) biology. 

The successful Candidate will be a junior postdoctoral researcher, with proven experience in data science and computer simulations in biomedical engineering. He/She will be based at DTIC, UPF and will be responsible for osteoporosis patient stratification based on both clinical and biomechanical information, and for the development of a meta (surrogate) biomechanical model of the femur and the vertebra, to estimate bone strength at reduced computational cost, in collaboration with 3D Shaper Medical SL. Scientific and technical competencies are necessary in modelling and machine learning in biomechanics. Previous experience in physics-based computer simulations and bone biomechanics are welcome. The Researcher will collaborate with a small team of researchers dedicated to the same project and will report periodically to the respective PI of UPF and 3D Shaper Medical SL, to ensure (i) that the timelines of the project and deliverables are met, and (ii) that the project results can be properly disseminated through scientific and medical congresses and journals. Hence, communication, teamwork and leadership skills will be chiefly important.

At UPF, the successful Candidate will evolve in the highly international environment of DTIC. There, he/she will be able to interact directly with the 60+ investigators of BCN MedTech who gather expertise in medical image analysis and processing, machine learning and data science, complexity analysis, medical devices, and computational biomechanics and biology. Daily working interactions related to the project shall mostly happen with the teams of both the BMMB and the SIMBIOSys group. While day to day working language will be English, Spanish language fosters social interactions and (the learning thereof) is highly recommended.


The employment for BONE STRENGTH shall be for a period of up to 1,5 years. The successful candidate will be offered a full-time postdoctoral research contract for the implementation of BONE STRENGTH. The number of working hours is 37,5 h per week and 1640 h per year. The gross salary is 33.715,68 € per year. On top of this, social benefits (health, unemployment, retirement) are covered by the employer (UPF).


Candidates must:

  • Hold a BSc and a MSc in either Computer Science, Applied Mathematics, Physics, or any related field
  • Have a PhD title, with a doctoral thesis focussed on Machine learning in biomedical engineering
  • Be able to demonstrate a proficient level of English, both written and spoken. Language certificate is not mandatory but proper English level will have to be demonstrated during the interview (see selection criteria)


1st phase: remote pre-selection (0-100 points): 

  • The Scientific, Technological & Academic excellence will be considered, based on:
  • A full CV that shall include, among others (0-70 points):
    – A description of the current or, in case of unemployment, of the more recent position
    Education and professional tracks
    – Research experience supported by evidence such as: scientific publications; patents; participation in scientific congresses; participation in research projects including any leadership information; …
    – International research collaborations
    – International mobility experience (research stays longer than three weeks)
    – Scientific mentoring activities: (co-)supervision of PhD, MSc and/or BSc theses; participation in scientific courses, workshops, summer or winter schools as instructor; … 
    – Roles in academia and/or in scientific societies 
    – Activities in science communication & outreach: press releases; online videos; participations to events for non-expert public; …
    – Recognitions and merits: individual competitive grants; awards, invited talks, …
    – A narrative biosketch with a section of the five major achievements of the CV   
  • Two reference letters provided by international scholars (0-15 points)
  • Statement of purpose: past research experience; motivation to apply to this position; academic fit; contribution of the project to future careers plans; … (0-15 points)

To pass to the 2nd phase (see below), the Candidate must have scored at least 75/100 during the remote review.

IMPORTANT: the publication records will be double checked through online databases (Web of Science, Scopus, Google Scholar, ResearchGate, ORCID, …). The Candidate is encouraged to provide the link of his/her choice in the CV. Failure to access to any online database of the scientific production of the researcher will justify the exclusion of Applicant from the selection process.

2nd phase: interview(s) (0-100):

Should the Applicant be preselected during the 1st phase, (s)he will be informed by email, for a 2nd phase of selection. The 2nd phase will consist in at least one interview through which:

  • the English language (eliminatory if deemed insufficient),
  • the motivation (0-15 points), 
  • the proactive behaviour (0-15 points), 
  • the capacity to work collaboratively (0-15 points), 
  • the organizational skills (0-15 points), 
  • the communication skills (0-15 points), and
  • the capacity to engage in a scientific discussion and manage problems (0-15 points), 

 will be assessed, among other aspects (0-10 points will be reserved for the general impression).

The interview must lead to a score of at least 75/100, so that the Candidate can be considered for the final decision.

Final decision 

The final decision will be the result of a consensus made by the Recruitment Committee that will consider the results of both selection phases 1 and 2. The Applicant will be informed of the selection outcome by email.

IMPORTANT: The referees might be contacted by the Recruitment Committee, to reach the final decision.


Post-doctoral Research Associate in Computational Spine Biomechanics @University of Sheffield

The Insigneo Institute is looking to appoint a Post-doctoral Research Associate in Computational Spine Biomechanics to work on the recently awarded Horizon Europe Project, METASTRA – Computer-aided effective stratification of oncologic patients with vertebral metastases for personalized treatment through robust and validated numerical tools. The project strives to provide a combination of models biomechanically validated and demonstrated in relevant clinical environments that will be incorporated in a clinical decision support system.

Working with Professor Damien Lacroix and Dr. Enrico Dall’Ara you will work to advance the modelling of patients with vertebral metastases for the prevention of fractures to reliably stratify patients based on their fracture risk.

We are seeking candidates with an excellent PhD in biomechanics (or a related discipline). A solid knowledge of finite element modelling, expertise in using finite element software with high level of sophistication (e.g. use of user-subroutines in Abaqus, Ansys) and experience of working as a team member to collaborate, co-operate and participate with others to achieve common objectives and to share experience and ideas is essential.

Deadline for applications: 26th April 2023 

To apply please visit this webpage:

Use as keyword: Metastra

And click on Apply!

More information:

Postdoc vacancy in microstructural imaging of blood vessels and tissue biomechanics @Erasmus MC / TU Delft.

Interested in diving into the fascinating world of microstructural imaging of blood vessels and linking this to tissue biomechanics? There is an open position for a post-doctoral researcher in the Biomechanics Group at Erasmus MC / TU Delft.

Application links and more info:

3 postdoctoral job offers in Computational Bone mechanics @UPF, Barcelona

We are offering three postdoctoral positions in the area of Biomechanics & Mechanobiology at BCN MedTech, Department of Information and Communication Technologies, University Pompeu Fabra, Spain, to work in computational biomechanics applied to fragile bone fracture prediction in clinical cohorts:

  • Data science & surrogate modelling (1.5 years, full time): Junior postdoctoral researcher with expertise in machine learning applied to biomedical engineering: – Deadline March 7th 2023
  • Open-source finite element code development & implementation (2 years, full time): Postdoctoral researcher with expertise in open-source finite element software and computational continuum mechanics: – Deadline March7th, 2023
  • Patient-Specific finite element modelling and computational bone biomechanics (Junior leader, 2.5 years, full time): Senior postdoctoral researcher with at least two years of postdoctoral research experience in bone finite element analysis: – Deadline: March 7th, 2023

Newton Fellowship in computational cardiovascular biomechanics

Newton International Fellowships are prestigious postdoctoral fellowships for researchers who want to work in the UK. The scheme is accepting applications now with a deadline of 28th March 2023. The fellowship provides three years of research funding, and only those with a PhD from outside of the UK are eligible. More details and eligibility criteria are available at

Do you have background in computational tissue biomechanics? Are you interested in cardiovascular systems and the above scheme? If so, check our Computational Biomechanics Research Group page or my staff page for more information on our research. We would be happy to host excellent researchers with relevant background and interests. Email me at if you would like to discuss this fellowship opportunity.

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