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 20^th, 2024.

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

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

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

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

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

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

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

More information:

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

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

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

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

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

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

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

LIST OF AVAILABLE PhD POSITIONS

Complete list of the 10 Doctoral positions available within REBONE:

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

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

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

https://lu.varbi.com/en/what:job/jobID:662804/type:job/where:4/apply:1

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

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

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

During this project, the student will have opportunities to:

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

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

Application: The deadline for applications is 31 January 2024, and the application process consists of two parts:
1) On-line academic application: Go to 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) School of Engineering EPSRC/School Scholarship Application via online portal: https://www.gla.ac.uk/ScholarshipApp/]gla.ac.uk/ScholarshipApp/ To complete the scholarship application, students will need a supporting statement from the proposed supervisor. Any queries about application procedure can be directed to eng-jws@glasgow.ac.uk

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.