ESBiomech24 Congress in Edinburgh

Postdoc position in Experimental Bone-Spine mechanics @University of Sheffield

Are you looking for an exciting PostDoctoral post in Experimental Bone/Spine mechanics?

Join us at Insigneo to work with Dr Enrico Dall’Ara and Prof Damien Lacroix on the recently EU funded METASTRA project!

This highly interdisciplinary post-doctoral position will advance our understanding of the biomechanics of metastatic spine and will create an experimental database for the validation of computational models for assessing metastatic vertebrae before and after treatment.

The position is within Insigneo and is funded as part of Horizon Europe/Innovate UK research project METASTRA (https://www.metastraproject.eu/) that aims to provide a combination of computational models biomechanically validated and demonstrated in relevant clinical environments that will be incorporated in a clinical decision support system.

This part of the project is focused on model validation using state of the art mechanical testing combined with imaging and digital volume correlation.

You will have an excellent PhD in biomechanics (or a related discipline), possess a solid knowledge of bone imaging and experimental biomechanics.

Ensuring the achievement of the project objectives will advance the vision of the Insigneo institute to validate computational models for the musculoskeletal system and produce a transformational impact on healthcare.

The PDRA will also sustain and strengthen collaboration within relevant Insigneo research groups and beyond; and will commit to Insigneo’s mission to produce high quality and impactful cutting-edge research. You will join the group of Dr. Enrico Dall’Ara and Prof Damien Lacroix. Our biomechanics group within the Department has an international and interdisciplinary profile and a strong commitment to clinical and industrial translation with impact in future healthcare. We are active in biomechanics and mechanobiology of the neuromusculoskeletal systems. We have access to a fully equipped human movement analysis laboratory, a tissue testing/mechanobiology laboratory, and to ex vivo and in vivo microCT imaging facilities

Link for Applications

Deadline applications: 6th December 2023

Tentative Start: 1st March 2024

Duration: 3 years

2 PhD positions in cancer mechanobiology @University of Galway

Applications are invited from suitably qualified candidates for multiple full-time, fully-funded positions that will investigate the mechanobiology of tumour growth and therapy resistance. These positions are funded by a European Research Council Starting Grant and will be under the supervision of Dr Eoin McEvoy, Assistant 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.

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 experimental and computational models for the prediction of cancer patient outcomes, leveraging the biophysical forces that underpin cell behaviour. PhD research topics will bridge subcellular remodelling, single cell mechanobiology, and macroscale tumour evolution to provide a new and fundamental understanding of tumour growth and therapy resistance in breast cancer. As part of the PhD programme (project dependent), you will receive training in computational and experimental cell mechanics, patient-derived tumour organoid generation, microfluidic cell culture, advanced microscopy, agent-based modelling, and/or advanced finite element analysis.

Application Deadline: Applications will be reviewed periodically until January 31st, 2024.

More information:

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:


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