ESBiomech24 Congress in Edinburgh

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

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

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

PhD position in computational cardiovascular mechanics @University of Glasgow

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

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

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

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

The PhD candidate will be involved in the following work:

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

[1] Soar and Tozzi, 2023. Data-driven image mechanics (D2IM): a deep learning approach to predict displacement and strain fields from undeformed X-ray tomography images – Evaluation of bone mechanics. https://www.biorxiv.org/content/10.1101/2023.09.21.558878v1

More information: https://www.jobs.ac.uk/job/DDK308/phd-studentship-in-data-driven-image-mechanics-d2im-a-deep-learning-approach-to-predict-displacement-and-strain-fields-in-biological-tissues-from-x-ray-tomography

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

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

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

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

The position will remain open until the position is filled. Applications should be sent to: Prof. Sara Checa (sara.checa@charite.de)

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

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

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

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

For applications, please see details below.

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

 Required skills:

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

Other valued skills (not mandatory):

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

Qualification system:

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

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

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

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

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

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

Further details and application link: https://www.cimne.com/vnews/m973/11967/vac-2023-49-%E2%80%93-postdoc-position-in-data-driven-modelling-for-endovascular-thrombectomy

University Assistant (Prae-Doc) in Computational Biomechanics @ TU Wien, Vienna, Austria

The Research Unit Computational Biomechanics, ILSB, TU Wien is currently looking for a university assistant (prae-doc) for 30 hours/week (for expected four years). The expected start is November 2023.

More information can be found by following this link:

https://jobs.tuwien.ac.at/Job/215947?culture=en

Application deadline: 21.9.2023

PhD position on neuro-musculo-skeletal analysis of human movement in real time including muscle fatigue @ University of Coruña

A pre-doctoral contract is offered (former FPI scholarships) at the University of Coruña (Spain), associated with the national project “Capture, reconstruction and neuro-musculo-skeletal analysis of human movement in real time, with consideration of muscle fatigue“, financed by the Ministry of Science and Innovation.

The project summary is as follows:

PhD position in multiscale modeling of the intervertebral disc to predict the relationship between of degenerative processes and systemic low grade inflammation @Universitat Pompeu Fabra

The Biomechanics and Mechanobiology (BMMB) research group is currently looking for a PhD Candidate working on multicellular models to describe the dynamics of the long-term mechanobiological regulation of the intervertebral disc (IVD), and the effect of low-grade inflammation on such immune-privileged organ.

The IVD lies within the vertebras, providing flexibility to the spine and is, therefore, constantly subjected to complex loading conditions. It reflects the biggest avascular structure of the human body, where cell nutrition is diffusion dependent. Hence, cells within the IVD are constantly subjected to a demanding loading and nutrition environment.

Dynamics at the (multi-) cellular level, related to this harsh environment are currently thought to be a main driving force in the dynamics of IVD degeneration, given the highly load-bearing capacity of the IVD at the organ level. IVD degeneration accounts for over 40% of cases of low back pain, which affects over 80% of the world’s population at least once in an individual’s lifetime, which emphasizes the need for investigation.

IVD degeneration is a slow process, developing over months to years without being perceived by the person, therefore, classified as a “non-communicable disease”. Research suggests that the presence of proinflammatory cytokines plays a critical role in IVD degeneration, and being possibly a major regulator of non-communicable diseases in general, which includes systemic diseases such as osteoarthritis (OA) and atherosclerosis (AS).

The European Research Council Consolidator Grant (ERC CoG) funded project O-Health (101044828) aims at shedding light to the role of low-grade inflammation in non-communicable diseases. This PhD thesis will be part of the O-Health research project, focusing on the relationship between low-grade inflammation and IVD degenerative processes.

Job description:

The PhD Candidate will develop in silico models to approximate the regulation of IVD degeneration with emphasis on the role of low-grade inflammation within the intervertebral disc. The work encompasses various in silico modeling techniques to cover the multiple spatial scales, i.e. from a subcellular up to a multicellular level, required to adequately model regulations of inflammatory and degenerative processes. Those techniques include primarily network modeling and Agent-based modeling approaches. The IVD multiscale model developed by the PhD Candidate forms part of a large network of interconnected models that simulate other non-communicable diseases such as OA and AS and their connection via the blood stream. Hence, the PhD candidate will tightly collaborate with a team of computer scientists, data scientists, biomechanicians and experts in (cell-)biology.

The work contract covers funding for a period of up to four years. It will be led by the BMMB research lab, which forms part of the research unit BCN MedTech, at the Department of Communication and Information Technologies (DTIC) of the University Pompeu Fabra (UPF) in Barcelona, Spain.

More information:

https://euraxess.ec.europa.eu/jobs/131905


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