10th World Congress of Biomechanics 2026 in Vancouver

 Postdoctoral researcher @  Arts et Métiers 

  • Localisation: ENSAM – Paris Campus 

  • Practical information: 

    • Position available from: 01/01/2025

    • Lab : Institut de Biomécanique Humaine Georges Charpak 

    • Emploi de catégorie: A 

    • Fixed term contract: 12 months, full-time 

    • Remote working: non-teleworking position 

    • Contract type: Post-doc 

    • Salary range (depending on experience and profile): 27k to 34k 

    • ENSAM has an active policy to support and promote equality, diversity and inclusion within its communities. 

    • We encourage applications from a wide range of backgrounds and all our positions are open to people with disabilities. 

  • Candidature : 

Who are we ? 

Since it was founded in 1780, the Ecole Nationale Supérieure Arts et Métiers (YouTubeLink) has been committed to meeting the ever-changing challenges facing industry and society. 

A public scientific, cultural and professional establishment (EPSCP) under the sole supervision of the Ministry of Higher Education and Research, it comprises eight campuses and three institutes spread across the country. 

Its primary mission is to train engineers capable of designing environmentally-friendly products and systems, as well as controlling industrial organisation while keeping risks and costs under control. 

Work environment 

The Institut de Biomécanique Humaine Georges Charpak (IBHGC, Arts et Métiers, Université Sorbonne Paris Nord), which was set up in 1979 and now has over 50 permanent staff, has made the strategic choice to focus on the osteoarticular and musculoskeletal systems, and to explore this system in a variety of ways towards subject-specific modeling of the human body. 

The IBHGC is developing research into the geometric and mechanical modelling of the neuromusculoskeletal system, the experimental in vitro characterisation of this system and the development of quantitative methods for exploring living organisms, with the motto ‘Better understanding for better innovation, at the service of patients and society’. 

The project behind this grant is the result of collaboration with UMRS 1158 ‘Experimental and clinical respiratory neurophysiology’ at Sorbonne University and the R3S department (‘respiration, réanimation, réhabilitation, sommeil’) at the Pitié-Salpêtrière Charles Foix Hospital Group. 

The team is composed by : 

Valérie Attali (MD-PhD), pulmonologist, UMRS1158 Experimental and Clinical Respiratory Neurophysiology, Inserm – Sorbonne University. 

Baptiste Sandoz (PhD, HDR), Associate professor, Institut de Biomécanique Humaine Georges Charpak, Arts et Métiers Sciences et Technologies. 

Damien Bachasson (PhD, HDR), INSERM research fellow, UMRS1158 Experimental and Clinical Respiratory Neurophysiology, Inserm – Sorbonne University. 

Claudio Vergari (PhD, HDR), professor, Institut de Biomécanique Humaine Georges Charpak, Arts et Métiers Sciences et Technologies. 

Laurent Gajny (PhD), Associate professor, Institut de Biomécanique Humaine Georges Charpak, Arts et Métiers Sciences et Technologies. 

Missions 

Working at the Institut de Biomécanique Humaine Georges Charpak and reporting to the Director, you will take part in the ANR BIO-DIAPHRAGME project: “Imaging the diaphragm and biomechanical biomarkers of postural dysfunction in chronic respiratory diseases”. The aim of this research project is to explore the neuro-mechanical coupling between the postural and respiratory systems, focusing on the essential role of the diaphragm. It focuses particularly on patients suffering from chronic obstructive pulmonary disease (COPD), a respiratory disease that progressively alters lung function and posture. 

As part of this interdisciplinary project, your mission will be to develop and evaluate a three-dimensional method for reconstructing the shape of the diaphragm using two X-rays of the face and profile in the standing position, in consultation with the project’s multidisciplinary scientific team. 

Activities 

Your activities will include: 

– Automatic or semi-automatic segmentation of the diaphragm on 3D imaging data (scanner, MRI). 

– Definition and parameterisation of an average 3D model of the diaphragm. 

– Development of a method for automatic analysis of face and profile X-rays: segmentation and annotation of anatomical landmarks. 

– Development of a method for deforming the average model on data obtained from face and profile X-rays. 

– Assessment of the accuracy of the proposed method. 

Aim 

The aim of this post is to provide an operational method for personalised three-dimensional reconstruction of the diaphragm in order to investigate potential biomechanical biomarkers of postural dysfunction in chronic respiratory diseases. 

Desired profile / Skills required 

– Solid programming skills, particularly in image analysis and deep learning are expected. 

– Solid mathematical skills, particularly in geometry and numerical analysis, are also expected. 

– A good level in mechanics, or even biomechanics, would be a plus. 

– Operational know-how 

– Adopt a quality approach to programming 

Personal skills 

– Curious, particularly about health issues, sociable. 

– You also have good listening and adaptation skills. 

Practical information 

Experience: Young researcher (PhD) 

Languages: French/English 

Academic level: Bac + 8 (PhD in computer science/computer vision, biomedical engineering or biomechanics) 

Keywords 

  • Biomedical engineering 
  • Medical imaging 
  • Artificial intelligence 

Advantages 

Joining Ensam means benefiting from a socially committed working environment: 

– Up to 50 days’ leave in your first year, depending on your work pattern 

– Mutual insurance contribution of €15/month 

– 75% contribution to public transport costs 

– Sustainable mobility package 

– Canteen, leisure, sport and culture offers 

Your personal data 

ENSAM processes your personal data in accordance with the RGPD and the French Data Protection Act. 

This processing is carried out for the purposes of managing your application and assessing your skills in relation to the post/internship for which you are applying. 

If you wish to exercise your rights regarding your personal data, you may contact ENSAM’s Data Protection Officer at dpo@ensam.eu 

For full details of the data collected by ENSAM and how your data is processed, you can consult ENSAM’s personal data protection policy HERE

2 PhD Positions within ERC STG Project AUTOMATHIC – Maastricht University

Two vacancies are available for ambitious individuals to join Maastricht University as part of the ERC STG project “AUTOMATHIC”. This 5-year interdisciplinary project aims to perform cutting-edge research in developing new methodologies for the automated modeling of the dynamic behavior of large biological networks. The project also involves engaging with national and international stakeholders. 

In silico models aim to capture and elucidate the complex and emergent interactions of biological systems, with the goal of expediting research and potential clinical translation. For example, ordinary differential equation (ODE) models of toxin and drug transport are being developed to bring safer therapies to chronic kidney disease patients. Despite recent progress, these cutting-edge ODEs only model transport in steady state and remain limited regarding the amount and complexity of dynamic transport mechanisms as it is often not clear which kinetic relation is most suitable. This limitation is due to the manual and labor-intensive approaches to construct the ODEs, which critically hinder their application in quantitative toxicity assessment in key industrial settings like drug development. In AUTOMATHIC, we aim to develop an integrated framework for automated ODE structure identification, parameter estimation and model evaluation and explore the capabilities of the developed framework for toxin and drug transport in the kidney. 

More information can be found here:

PhD Position: Framework for automated ODE model construction Job Details | Maastricht University

PhD Position: Automated Knowledge Graphs for Kidney Physiology and Pathology Job Details | Maastricht University

PhD: Advanced material-based regenerative approach for degenerative spinal disorders – Eindhoven University of Technology

Short Description
– Are you eager to develop innovative regenerative fusion technologies to treat back pain?
– Are you inspired to push the boundaries on engineering biomaterials to address medicine’s future needs?

Job Description
Back pain is among the top ten diseases causing the greatest burden on society in terms of years lived with disability. It is estimated that 30 to 40% of these cases are attributed to intervertebral disc (IVD) degeneration. Currently, there are no satisfactory treatments for IVD degeneration. If analgesics and physical therapy fail to control the pain, operative treatment can be considered in some cases, where the involved spinal segments are fused using metal/polymer cages. Such spinal fusion operations are very effective in relieving patients’ pain, but they are not always successful, sometimes leading to delayed fusions or non-unions. Our goal is to develop an innovative solution for spinal fusion using a 3D printed bioresorbable ceramic-based cage that is osteoinductive, load-bearing, and can counteract local inflammation. The newly created implant will be tested in vitro and in an in vivo animal model to move one step closer towards translation to human clinical applications. Your aim will be to design, fabricate, and characterize a subject-specific cage implant that promotes spinal fusion through mechanical stimulation while providing adequate mechanical strength until complete vertebrae fusion. To do this, you will focus on modeling the mechanobiology of the native tissue using integrated computational and experimental methods and translate those findings into innovative regenerative designs and material implants that promote fast and complete spinal fusion. You will contribute to a large Dutch-Brazilian research program – BioFusion – to research engineered biomaterials for spinal fusion (more details here). You will closely collaborate and spend some time at our partner organizations at KU Leuven (Belgium) and UNESP – Universidade Estadual Paulista, School of Engineering (Brazil).

About the group
You will be enrolled at Eindhoven University of Technology within the Biomaterials Design and Processing and Orthopedics groups. Our mission is to develop novel treatment strategies for an aging and active population. We combine advanced biomaterials and manufacturing methods, such as Additive Manufacturing and Bioprinting, with in vitro, ex vivo, and in vivo platforms, as well as engineering methods like high-resolution imaging and computational modeling. Our goal is to enhance understanding of musculoskeletal tissues and create regenerative treatments. We are part of the Regenerative Materials and Engineering cluster in the Department of Biomedical Engineering. The department offers Bachelor’s and Master’s programs linked to research areas such as Chemical Biology, Biomaterials, and Biomechanics, with over 800 students and 200 academic staff. Our inclusive, collaborative campus fosters connections and excellence in research and education.

Job Requirements
We are accepting applications from enthusiastic and highly talented candidates who meet the
following requirements:
– A master’s degree (Second Cycle qualification) in Biomedical engineering, Mechanical engineering, Material Science and engineering, or related discipline.
– A solid background in continuum mechanics and biomechanics.
– A strong interest in computational mechanics, mechanobiology and multi-scale material modelling.
– Experience with bone engineering, inorganic biomaterials and Additive Manufacturing is preferred
– Excellent programming (e.g. Python, Matlab) and data analysis skills.
– Strong motivation to do excellent, original, fundamental research.
– Team player and able to work in a dynamic, interdisciplinary, and international context
– Excellent written and oral communication skills. Note that there is no Dutch language requirement.
– Motivated to develop your teaching skills and coach students.

Conditions of Employment
We offer a meaningful job in a dynamic, stimulating and ambitious team environment.
– A full-time employment contract for four years, with an intermediate performance review after nine months.
– A gross monthly salary and benefits that align with the Collective Labor Agreement for Dutch Universities.
– Additionally, an annual holiday allowance equal to 8% of your yearly salary, and a year-end allowance of 8.3% of your annual salary.
– A broad package of fringe benefits, including access to an excellent technical infrastructure, assistance with moving expenses, and participation in savings schemes.
– Family-friendly initiatives, such as an international spouse program, on-campus children daycare, and sports facilities.
– Cutting-edge research focused on bone fractures and will receive innovative multidisciplinary and multisectoral training from experienced supervisors in both clinical and academic fields.
– Be part of an international team of biomaterials and spine research experts and a large network of PhD students.
– Secondments at KU Leuven (Belgium) and UNESP – Universidade Estadual Paulista, School of Engineering (Brazil)
– A structured training program, which includes a combination of soft skill courses, targeted workshops, social events, and networking opportunities.

Information and application
Do you recognize yourself in this profile and would you like to know more? We invite you to submit a complete application directly to dr. Miguel Castilho (m.dias.castilho@tue.nl). The application should include a:
– Cover letter in which you describe your motivation and qualifications for the position.
– Curriculum vitae, including a list of your publications and the contact information of three referees.
– Copies of degree and academic transcripts (with grades and rankings), for both the Bachelor’s and Master’s degrees. Academic records not written in English should be accompanied by a translation into English (it can be either an official translation or self-translation). If the candidate has not been awarded the qualifying degree yet, he/she should provide a document proving the expected date of award.

DC8– Mechano-chemo models of the knee and intervertebral disc joints, to explore the emergence of age-related risk factors of degeneration

1. Overview of the research programme:

InSilicoHealth is an innovative Doctoral Network (DN) with the ambition to train a new generation of outstanding Doctoral Candidates (DC) that will become effective translators of the rapidly evolving digital technology to tackle existing and future challenges related with healthy ageing in Europe. The research focus of this DN lies in three key domains: the brain, heart, and musculoskeletal (MSK) systems. In the realm of digital technology, InSilicoHealth specifically focuses on virtual human twin (VHT) technology to enhance our understanding of the age-related adaptive changes of the complex human body through predictive multi-scale simulations. The research methodology employs knowledge-driven models enhanced by advanced data-driven inference techniques to optimize the health potential of older individuals.

2. Individual PhD Project Information:

Host institution: Pompeu Fabra University (UPF), Spain

Supervisory team: Prof. Jerome Noailly (PhD supervisor, UPF), Prof. Ilse Jonkers (PhD co-supervisor, KU Leuven), Prof. Miguel Ángel González Ballester (PhD co-supervisor, UPF), Dr Ludovic Humbert (secondment host, 3D-Shaper).

Enrolment in Doctoral School: Enrolled in the Information and Communication Technologies (UPF) and at the Doctoral School of Biomedical Sciences (KU Leuven).

3. PhD project description:

This PhD project will focus on coupling biological regulatory network and organ finite element models to define risk factors of different rates or organ ageing in personalised models related with patient (osteoarthritis, low back pain) and population cohorts, with which UPF works. The objectives are: 1) Couple pre-existing models at UPF: chondrocyte and intervertebral disc mechano-sensitive cell regulatory networks models with finite element models of the knee joint and the intervertebral disc; 2) Personalise the shapes of the organ models by combining magnetic resonance image segmentation and mesh morphing; 3) Personalise the regulatory network initial states, based on patient BMI, age and other factors known to control low grade inflammation mediators mapped in the networks; 4) Run simulations and mine together input data for model personalization and simulated data related with network node activations that reflect nociceptive pain, pro-inflammatory cytokine activity, balance between matrix proteases and inhibitors thereof, structural proteins; 5) Define a pipeline for model assessment, based on uncertainty and consistency analyses, falsification tests against clinical cases, capacity for discrimination in clinical case-control: 6) Assess risk factors and build corresponding surrogate models.

A successful project will result in a robust pipeline for multiscale modelling that allows mechanistic explorations of pathophysiological mechanisms and risk factor predictions for age-related joint degeneration, based on interpretable biological mechanisms.

4. Planned secondments:

  • KU Leuven (December year 2, 6 months): Aims to personalise the mechanical boundary conditions to be imposed on the knee joint and intervertebral disc models, based on the movement signatures investigated by DC7, and on the translation thereof into mechanical loads to be applied on the joints, through existing collections of motion capture and MSK analyses at KU Leuven (knee joint), and through existing measurements of in vivo intervertebral disc pressure under daily activities (intervertebral disc).
  • 3D-Shaper Medical (May year 1, 4 months): Early secondment at 3D-Shaper Medical aims to explore robust pipelines for personalised modelling of knee joints, through machine-learning based image processing allowing advanced annotations and fast 3D modelling, out of X-rays and MRI.

5. Essential requirements:

  • You hold both a Bachelor’s and a Master’s degree in Biomedical Engineering, Biomedicine, Computer Science, Industrial Engineering, Mechanical Engineering.
  • Specialization in computational methods in biomedical engineering or biomedicine will be highly beneficial.
  • You have a keen interest in the fields of in silico medicine, digital health, and rheumatology.
  • You have proven your proficiency in English language equivalent to B2 level (Sufficient English level will be verified during the interview, if any).
  • You did not reside or carry out your main activity (work, studies, etc.) in the host institution’s country for more than 12 months in the three years before 1st of January 2025.
  • You are ambitious, well organized, a team player, and have excellent communication skills.
  • You can work independently and have a critical and analytical mindset.
  • You are a pro-active and motivated person, eager to participate in network-wide training events, international mobility, and public dissemination activities.
  • Previous experience in finite element modelling, and/or medical image processing, and/or data science, and/or motion capture and analyses, are not required but considered a plus.

6. Application requirements:

  • Curriculum vitae.
  • Motivation Letter, including a clear indication of the preferred DC position(s) within InSilicoHealth Doctoral Network if the applicant postulates for multiple positions.
  • Academic records (grades) of both the Bachelor’s and Master’s degrees.
  • Two recommendation letters by two previous scientific supervisors (these people might be contacted by the Evaluation Committee of the position, if needed).

PhD Position University of Glasgow – Computational Biomechanics Research Group

Are you interested in undertaking a PhD in the interdisciplinary field of computational cardiovascular biomechanics? If so, there are positions available in my research group and details are provided below.

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

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, including, but not limited to:

1) Predicting aneurysm development from ultrasound images using growth and remodeling simulations
2) Drug-based treatment of aneurysms: a computational study
3) Uncertainty quantification in image-based cardiovascular biomechanics
4) Image-based cardiovascular diagnosis using machine-learning
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 excellent grades. 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 2025, and the application process consists of two parts:
1) On-line academic application: Go to https://www.gla.ac.uk/postgraduate/research/infrastructureenvironment/ and click on the ‘Apply now’ tab. Applicants should attach relevant documents such as CV, transcripts, references and a research proposal.
2) Scholarship: Depending on the eligibility, you can apply for competitive scholarships, such as UofG School of Engineering Scholarship, CSC Scholarship, Commonwealth Scholarship, etc. These are listed on https://www.gla.ac.uk/colleges/scienceengineering/graduateschool/scholarships/#pgrscholarships Please feel free to get in touch to discuss further.

PhD Position in Computational and Experimental Mechanobiology (Cancer) @University of Galway, Ireland

Applications are invited from suitably qualified candidates for a full-time, fully-funded position that will investigate the mechanobiology of tumour growth and therapy resistance. This position is funded by a European Research Council Starting Grant and will be under the supervision of Dr Eoin McEvoy, Associate 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 www.mechanomodel.ie.

University of Galway: The University of Galway has world-recognized expertise in biomedical science and engineering, with a particularly strong track-record of developing innovative diagnostic and therapeutic solutions to healthcare challenges. Located in the vibrant cultural city of Galway in the west of Ireland, with over 18,000 students and more than 2,400 staff, the university has a distinguished reputation for teaching and research excellence (https://www.universityofgalway.ie/our-research/). Dr McEvoy is also an investigator at CÚRAM, the Science Foundation Ireland Research Centre for Medical Devices, which is embedded in Galway’s vibrant Med-Tech ecosystem.

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 computational and experimental models for the prediction of patient-specific cancer cell behaviour, to uncover new mechanistic insight and advance multi-scale models. Specifically, the candidate will develop (i) novel microfluidic systems to characterise active cell biomechanics and (ii) coupled predictive models using advanced finite element analysis and agent based modelling. This frontier research will bridge subcellular remodelling and single cell mechanobiology to provide a new fundamental understanding of tumour growth and therapy resistance in breast cancer.

Stipend: Fully-funded four-year scholarship – €22,000 per annum (tax-exempt award). University fees are fully covered by the scholarship. You will also receive a high-end laptop or desktop computer for your research. Travel expenses are included to attend frontier international conferences.

Academic entry requirements: Applicants must hold a Bachelor’s degree in Biomedical or Mechanical Engineering, Applied Maths or a related field. Prospective candidates should be enthusiastic, motivated, and willing to learn new skills.

Start Date: October 2024 – January 2025; the position will remain open until filled.

How to Apply: Interested candidates should send their CV (including the names of two referees) and a one-page cover letter outlining their motivation to work on the project to Dr Eoin McEvoy at eoin.mcevoy@universityofgalway.ie. Please use the email subject line “PhD Application” to ensure that applications are processed. You are also welcome to reach out for an informal discussion on the available projects and positions.

Application Deadline: Applications will be reviewed periodically until September 20th, 2024.

For more information on moving to Ireland, please see www.euraxess.ie

PhD position on mechanobiology of bioengineered microvascular networks @KULEUVEN

Applications are invited for a Ph.D. project position within the MAtrix / Mechanobiology & Tissue Engineering research group (www.mech.kuleuven.be/mechanobiology), a bioengineering group that is pioneering the role of cellular forces for microvascular formation and function in health and disease. The group is led by Hans Van Oosterwyck and is one of the few groups worldwide that has established 3D Traction Force Microscopy (TFM) routines and workflows for quantifying cellular force exertion in 3D, and routinely applies them to in vitro models of angiogenesis (endothelial invasion). Together with its research partners, it is currently developing novel in vitro models, compatible with TFM, to study the interplay between cellular force exertion, matrix mechanics and fluid flow, and how this interplay contributes to microvascular lesion formation within the context of specific (genetic) diseases.

Unit website

Project

Cerebral cavernous malformations (CCM) is a microvascular disease characterized by abnormal brain microcapillary beds resulting from mutations in CCM-complex genes, with no current cure. While we have recently demonstrated the significance of aberrant cellular forces for CCM lesion formation in 3D endothelial monoculture systems (see doi: 10.1101/2023.11.27.568780), more complex co-culture systems are needed to better mimic the environment of in vivo lesions. This project centers on deciphering the intricate interactions between endothelial cells (ECs) and pericytes within an advanced vessel-on-a-chip model. By integrating a 3D microfluidic platform with force quantification methods, the study aims to comprehensively elucidate the roles of EC and pericyte forces in CCM progression, emphasizing the dynamic interplay between biochemical and biomechanical factors. Beyond advancing vessel-on-a-chip technology, the project holds promise for broader applications in microvascular disease.

Profile

We are looking for a highly motivated, enthusiastic and communicative researcher with a master’s degree in biomedical engineering, biotechnology or a related field. The candidate should have obtained excellent study results. In addition, we require:

  • experience with basic cell culture techniques, optical microscopy, preferably live cell imaging in 3D (confocal microscopy, fluorescence microscopy).
  • some experience with or exposure to scientific computing (such as finite element modelling) and programming (such as Matlab).
  • a strong interest in mechanobiology and mechanotransduction.
  • a collaborative attitude, passion for research, creativity

Offer

We are offering an exciting Ph.D. position in a multidisciplinary, international and collaborative research environment. The MAtrix / Mechanobiology & Tissue Engineering group is working on cutting-edge methods for cellular force inference and is addressing important questions in vascular (mechano)biology in close collaboration with its biomedical partners. The group is based at the Leuven Chem&Tech / Leuven Nanocentre (https://set.kuleuven.be/chemtech_nanocentre) that forms the perfect environment for technology development and that houses unique equipment related to e.g. optical microscopy and nanoscopy, micro-, nano- and biofabrication and biosensing. KU Leuven is one of the oldest universities in Europe, with a very rich tradition in research and higher education. Today, it is among the best 100 universities in the world according to both Times Higher Education World Rankings and QS World University Rankings, and was ranked by Reuters as most innovative university of Europe since 2016. Leuven is a vibrant student town at the heart of Belgium and Europe, offering a great quality of life.

The group works in close collaboration with dr. Eva Faurobert at the Institute for Advanced Biosciences (University of Grenoble, France) and profs. Liz Jones, Aernout Luttun, Rozenn Quark and An Zwijsen (Centre for Molecular and Vascular Biology at KU Leuven), with whom you are expected to closely collaborate as well.

research group website
general information on working conditions
gross salary (salary scale 43)

Interested?

For more information please contact prof. Hans Van Oosterwyck, mail: hans.vanoosterwyck@kuleuven.be, Dr. Jorge Barrasa Fano, mail: jorge.barrasafano@kuleuven.be, Dr. Jyotsana Priyadarshani, mail: jyotsana.priyadarshani@kuleuven.be.

You can apply for this job no later than August 21, 2024 via the online application tool

More information: https://www.kuleuven.be/personeel/jobsite/jobs/60354466?lang=en

Senior Lecturer and Theme Lead in AI for Health @University of Sheffield

The Centre for Machine Intelligence (CMI) at The University of Sheffield wish to recruit a Senior Lecturer (Grade 9, equivalent to Associate Professor) in AI for Health.

The CMI is a strategic initiative supported by a £3.64m investment, dedicated to the transformation and acceleration of research, innovation, and teaching on and with AI. This position is one of four academic theme lead appointments. You will work across the CMI and related institutes (the Insigneo Institute and the Healthy Lifespan Institute) for the first three years of the post, after which you will join a School in the Faculty of Health or Faculty of Engineering appropriate to your disciplinary background and expertise.

AI for Health is a key research theme at the University of Sheffield. The recent award of a £4m EPSRC Digital Health Hub offers many opportunities at the interface of AI and health technology, and the University has invested £1.6m in Data Connect, a service to broker access to health data for research. We have strong links with one of the largest NHS trusts in the UK – Sheffield Teaching Hospitals NHS Trust – and with the Sheffield Children’s NHS Foundation Trust. World-class research is undertaken on a broad range of areas including in-silico modelling, digital twins, cancer, cardiovascular disease, medical imaging, health economics/decision science, neuroscience, infection/immunity, and public health.

You will have a background in computational research with digital healthcare data, with a track record in machine learning/AI methodology and its application. You will have direct experience of interdisciplinary collaboration using data from across healthcare sectors. You will have the skills to provide leadership in AI and health, and to work with other theme leads and the Centre Director to ensure that the CMI is at the forefront of AI research, innovation, and impact, nationally and internationally.

More information and application:

https://www.jobs.ac.uk/job/DIG334/senior-lecturer-and-theme-lead-in-ai-for-health

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 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

New 4-year PDRA position @ University of Glasgow

deadline 11th July 2024

The University of Glasgow is offering a unique opportunity for a Research Associate to make a leading contribution to the Centre for Future Percutaneous Coronary Intervention Planning.  The vision of the Centre is to develop novel and robust mathematical and statistical methodologies, supported by large clinical data sets, to create computational tools for optimisation of cardiovascular procedures. Based within the James Watt School of Engineering, you will work closely with colleagues from Mathematics & Statistics, Cardiovascular & Metabolic Health and Politecnico di Torino, as well as several leading international clinical centres and medical devices/imaging companies. 

You will work on the development of a range of mathematical models and their numerical solution, covering areas including patient geometry reconstruction, fluid-structure interaction, soft tissue mechanics, growth and remodelling and multiphysics modelling. You should have a PhD, or have equivalent experience, in Applied Mathematics, Physics, Computational Engineering, or a related discipline. You should have theoretical and practical knowledge of building multiphysics mathematical models and numerically solving them. Experience in patient geometry reconstruction from medical imaging, soft tissue mechanics and fluid-structure interaction modelling would be desirable.

You will also be expected to contribute to the formulation and submission of research publications and research proposals as well as help manage and direct this complex and challenging project, as opportunities allow.

For more details on the vacancy (147648) and to apply,  please visit the university webpage here: https://my.corehr.com/pls/uogrecruit/erq_jobspec_version_4.jobspec?p_id=147648

Informal enquiries about the role are welcomed, and should be addressed to Dr Sean McGinty, sean.mcginty@glasgow.ac.uk


Corporate members of the ESB:

AMTI force and motion logo
BERTEC logo
Beta CAE logo
BoB Biomechanics logo
Materialise logo
Nobel Biocare logo
SHL Medical logo