ESBiomech25 Congress in Zurich

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

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

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 e.dallara@sheffield.ac.uk


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: https://jobs.leeds.ac.uk/vacancy.aspx?ref=EPSME1154 (for the research assistant role, check your UK working eligibility by contacting InternationalHR@leeds.ac.uk)
  2. post-doctoral research (research fellow requiring a PhD) in knee and hip biomechanical evaluation: https://jobs.leeds.ac.uk/vacancy.aspx?ref=EPSME1155
  3. PhD student in spine biomechanics: https://phd.leeds.ac.uk/project/1826-integrating-morphology-and-mechanics-developing-a-statistical-shape-and-appearance-model-ssam-for-spinal-health-assessment-intervention-planning
  4. PhD student in bone healing: https://phd.leeds.ac.uk/project/1820-computational-biomechanical-modelling-of-external-fixation-of-fractures-to-predict-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.

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:


Corporate members of the ESB:

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