ESBiomech24 Congress in Edinburgh

Fully funded PhD studentship | 3D human pose estimation and shape reconstruction for biomechanics |

Closing Date: Review of applications will commence on 1 August 2020 and remain open until filled

Department: Bioengineering, Faculty of Engineering.

Applications are invited for an exciting fully-funded PhD studentship at the Faculty of Engineering, the University of Nottingham.

Research area. The research topic focuses on developing computer vision and machine learning based solutions that enable in-natura markerless motion capture for biomechanical modelling in Biomedical and Sports Engineering. Specifically, it addresses the fundamental research problem of reconstruction of person-specific human pose, kinematics, and surface geometry to enhance our understanding of the non-linear behaviour of human motion, musculoskeletal injury and disease and enable modelling of soft-tissue dynamics and human-object interaction.

The project. The candidate is expected to develop a fast and robust method for inferring and tracking 3D human pose and surface geometry. The method will be mainly based on visual sensing complemented by Inertial and force sensors. The method can use either or both of model-based and learning-based approaches, such as CNN based segmentation, geometric CNNs, or convolutional kernel filter based tracking. The candidate will have access to a newly established state-of-the-art motion capture laboratory.

The candidate. The ideal candidate will have;

  1. a first or upper second class honours or Masters degree in Electrical and Electronic Engineering, Physics, Computer Science, or other relevant and equivalent degree from a quality recognised institution.
  2. a solid background in mathematics and excellent analytical and numerical skills, as well as problem solving skills
  3. strong background in 3D computer vision, pose estimation, shape reconstruction, structure from motion, segmentation, or object detection.
  4. experience in image or video processing and digital signal processing.
  5. strong programming skills in Matlab, C/C++, or Python. Previous hands-on experience with deep learning platforms and agile software development as well as experience of working within industry will be an advantage.
  6. very good written and communication skills and fluency in English.
  7. a driven, independent professional and self-reliant work attitude within a fast-paced & collaborative environment.

The offer. The scholarship on offer (to eligible students) is for a minimum of three years and includes a tax-free stipend of 15,285 per year (for 2020/21) and tuition fees. It is available to students of UK and EU nationality. Applicants must obtain the support of the potential supervisor prior to submitting their application.

Informal enquiries about the project may be addressed to Dr Ami Drory. Please (i) insert your cover letter, CV, copies of academic transcripts, a list of publications, and contact details for two academic referees into a single pdf file. (ii) Name the file with your name as ”firstName_lastName_phd”. (iii) e-mail to: Ami.Drory [ at ] nottingham.ac.uk, with [3D shape reconstruction PhD application – lastName] as the email subject. Applications without academic transcripts or academic referees will not be considered. Applicants are advised to include copies of any publications or examples of their technical writing, such as code projects, project report or dissertation in support of the application.

Application instructions. With the support of the potential supervisor, formal applications are to be made via http://www.nottingham.ac.uk/pgstudy/apply/applyonline.aspx.

Closing date for applications. Review of applications will commence on 1 August 2020 and remain open until filled. A start date is expected to be as soon as practical thereafter.

2x PhD positions starting in November 2020 @University of Bologna

GENERAL INFORMATION

About this doctorate program

This PhD program has a duration of 3 years. The Doctorate in Health and Technology is an interdisciplinary program, where each PhD student has a supervisor from the technical area (engineering, chemistry etc) and one from the clinical or biological area.

https://www.unibo.it/en/teaching/phd/2020-2021/health-and-technologies

The objective of the interdepartmental Doctoral Programme in Health Sciences and Technologies is to train the next generation of leaders in industrial, clinical, and academic research. Our goal is to develop an organic research programme at the interface between engineering and medicine, which is inspired by the quantitative and integrative approach of physical sciences, and by the latest development in biomedical research, drive the development and clinical translation of disruptive health technologies.

The doctoral training programme will prepare students in conducting research which:

– Extend the comprehension of how human physiology and pathology work in term of physical and chemical mechanisms, and how these mechanisms respond when perturbed by external factors such as therapies, changes in life style, and environmental factors.

– Develop new technologies that by leveraging on this mechanistic understanding pursue a wide spectrum of applications relevant to human health, including prevention, diagnosis, prognosis, treatment, and rehabilitation.

How to apply:

Formal application must be submitted through the UniBo portal:

https://www.unibo.it/en/teaching/phd/information-enrolling-phd-programme/how-to-apply-phd-programme

Each student, depending on their degree, will be able to apply only for a sub-set of projects among those advertised for this PhD program; among them each student will be allowed to select three projects, and name them in order of preference; however, in some cases it might not be possible to satisfy all requests, and some students might be offered a research project different from those they selected.

The full call is available online:

https://www.unibo.it/en/teaching/phd/2020-2021/attachments/cycle-36-call-for-applications/@@download/file/36thCycle_CallForApplications_Def_Web.pdf

Profile of the candidate

We are looking for a highly motivated young researchers with a Master degree (or equivalent) in Mechanical Engineering, Biomedical Engineering, Physics, Material Science, or related disciplines, willing to study and do research at the leading edge of biomechanical engineering, in close contact with a clinical environment.

Individuals expecting to obtain their Master degree before 31 October 2020 can conditionally apply. In order to be admitted to the selection, a student needs a five-year higher education degree, which includes at least one module for each of the following disciplines: mathematics, physics, computer science, biology, physiology, and anatomy.

Candidates must be fluent in English as it will be the language used to interact with supervisors and colleagues during the project, and to interact with partners. Although some understanding of Italian may be useful for daily living, this is not a mandatory requirement. Communication and team-working skills are required in our international team.

Deadline:

Applications must be submitted through the Unibo portal by 21 May 2020, 13:00 Italian time (UTC +1)

Selection procedure: selection takes place in two phases. First the documents submitted by the applicants are examined, with no interaction with the candidates (early June). The eligible applications are shortlisted and the candidates are informed. In the second stage, the shortlisted candidates are interviewed. All interviews are performed remotely, in videoconference (mid-June).

Salary: 19 367 € per year before taxes.

More information: Perspective applicants are encouraged to contact Professor Luca Cristofolini

luca.cristofolini@unibo.it for informal discussion about the research projects.


PhD PROJECT #1:

Biomechanical evaluation of knee mechanical behaviour and interface stresses with a new concept of alignment for total knee arthroplasty (NEW-KNEE)

Summary

At least one knee replacement out of 5 are dissatisfactory due to continuous pain. This is mainly related to inadequate joint kinematics with the current paradigm for prosthesis alignment, causing painful patellar motions and poor balance of soft tissue. Recently, a different rationale has been proposed based on kinematical alignment (KA). This PhD student will work under the joint supervision of an orthopaedic surgeon focusing on knee replacement, and of two engineers with a background in biomechanical in vitro testing, and numerical modelling respectively. During these three years, the PhD student will develop a numerical to estimate how the knee joint loads are affected by implant positioning, and a series of in vitro tests to measure how this affects the implant-bone interaction.

Objectives of this project

The overall objective of this PhD project is to evaluate in vitro the biomechanical effectiveness of the kinematical alignment (KA) method for total knee arthroplasty (TKA).

The following specific objectives will be tackled:

• How the stresses at bone-prosthesis interface change with the KA alignment respect traditional mechanical alignment (MA)

• How bone stresses propagate in the distal femur and proximal tibia during specific motor tasks

• How the KA alignment interferes with the kinematics of the knee and if there is a threshold of safety in degrees from a mechanical neutral axis

• if KA alignment requires a specific prosthetic design (from the already present on the market) to be successful

This project covers some basic science (improving the understanding of knee biomechanics), it focuses on technological development (implementing a modeling strategy for the human knee) and has clinical relevance (improving the outcome of knee replacement).

The research team

This candidate will have an engineering background. While this will facilitate him/her in grasping the technical part of the project, some time and effort must be dedicated at the beginning to improve his/her understanding of the clinical problem. This project is rooted between three groups:

– The group of Prof. Cristofolini (Department of Industrial Engineering) will provide “training through research” in the area of biomechanics and material characterization. Prof. Marco Viceconti will be the supervisor for all computational aspects.

– The group of Prof Traina will provide training and supervision on the surgical procedures for tendon and ligament repair, on complications, and will supervise the design of the implantation technique.

Prof. Traina and prof. Cristofolini have been intensively collaborating for over 15 years on research projects at the intersection between orthopaedic clinical application and biomechanics research, and specifically on total joint replacement. A strong integration of the two research groups has been achieved by involving the clinical staff in lab activity, and the lab staff in clinical research. This PhD candidate will enjoy this extremely stimulating interdisciplinary environment, and will share his/her research time between clinics (in tight collaboration with Rizzoli Orthopaedic Institute) and biomechanics lab.

The Department of Industrial Engineering includes a large Biomechanics lab that is extremely active in the field of orthopaedic biomechanics. The focus of the biomechanics group directed by prof. Cristofolini within DIN is on the multi-scale biomechanical characterization of skeletal structures and orthopaedic devices, and on the integration of in vitro tests and numerical modeling. Their group, in collaboration with the Electrospinning group, recently developed and characterized innovative regenerative scaffolds. Furthermore, this group is acknowledged internationally for the applications of DIC to biomechanics.

The Dept. of hip and knee primary and revisions prosthetic surgery of Rizzoli Orthopaedic Institute is nationally recognized for the treatment of severe hip and knee conditions primarily through joint replacements. Its activity is mainly focused on surgical treatment of complex cases, analysis and data collection of multiple type of joint replacement surgery through different surgical approach and procedures. Comparison between different procedures and cases are routinely performed in order to continuously improve the patient’s provision of care and to develop innovative implant design and surgical tools The Labs of the Department of Industrial Engineering are equipped with the testing facilities required for this project, including:

– Approved procedures and dedicated space and facilities for safe storage, preparation, testing and disposal of biological tissue specimens (both human and animal)

– Five universal testing machines

– A proprietary multiaxial simulator for biomechanical testing

– State-of-the-art digital image correlation (DIC) system (4-camera system, up to 100 frames per second).

– Access to the In Silico Medicine group computational infrastructure, including high-level workstations, secure storage for clinical data within IOR network, and to a collection of specialised software tools for musculoskeletal dynamics modelling.

Specific skills useful for this PhD project

The following skills will be considered during the selection: good laboratory practice; mechanical testing and experimental stress analysis; handling and testing of biological tissue; orthopaedic biomechanics; mechanical properties of living tissues; Bone biomechanics; Soft tissue mechanics; Prosthetics; in vitro biomechanical testing; experimental stress analysis (digital image correlation); statistics and design of the experiment.

References

1. Howell SM, Kuznik K, Hull ML, Siston RA. Results of an initial experience with custom-fit positioning total knee arthroplasty in a series of 48 patients. Orthopedics. 2008;31:857–863.

2. Abdel MP, Ollivier M, Parratte S, Trousdale RT, Berry DJ, Pagnano MW. Effect of Postoperative Mechanical Axis Alignment on Survival and Functional Outcomes of Modern Total Knee Arthroplasties with Cement: A Concise Follow-up at 20 Years. J Bone Joint Surg Am. 2018 Mar 21;100(6):472-478.

3. Eckhoff DG, Bach JM, Spitzer VM, Reinig KD, Bagur MM, Baldini TH, Flannery NM. Three-dimensional mechanics, kinematics, and morphology of the knee viewed in virtual reality. J Bone Joint Surg Am. 2005;87 Suppl 2:71-80.

4. Castagnini F, Sudanese A, Bordini B, Tassinari E, Stea S, Toni A. Total Knee Replacement in Young Patients: Survival and Causes of Revision in a Registry Population. J Arthroplasty. 2017 Nov;32(11):3368-3372.


PhD PROJECT #2:

Understanding the causes of junctional failure in lumbar spine fixation through retrospective clinical analysis and in vitro tests

Summary

Fixation of the lumbar spine is associated with a high failure rate, both in young and in elderly patients. This project is expected to improve the general understanding of spinal biomechanics, the effect of different treatment options, including the detrimental effect of some surgical treatments. The main focus will be on the failure of the disc caudal to the fixation (junctional pathology).

This project will start from a retrospective analysis of clinical cases available within the Rizzoli database. The focus will be on the determinants for failure after corrective spinal surgery, including both patient-specific ones (anatomical, radiographical, etc.) and surgical ones (type of correction used).

On the experimental side, we will apply digital image correlation (DIC, a powerful experimental technique to measure deformations during in vitro mechanical tests) to analyze functional spinal units (FSU) and multivertebrae segments. DIC allows investigating both hard and soft tissue at the same time, providing a full-field view of the spine specimen. The focus will be on the biomechanical condition of the intervertebral discs after a range of spine surgery procedures.

Objectives of this project

The purpose of this 3-years project is to improve the understanding about the mechanism leading to failure after fixation of the lumbar region of the spine, with a main focus on the instability associated with failure of the caudal disc (junctional pathology) [1. 2]. While the incidence and consequences of such failures are known, the biomechanical causes are still unclear. In fact, different approaches have been proposed to mitigate this problem, with limited success. One causes of failure for such attempts has been the lack of interdisciplinarity: the surgical technique and instrumentation has been modified, without a strong biomechanical background.

This PhD candidate will integrate his/her clinical background, with dedicated training in biomechanics. He/she will apply in vitro tests to analyze functional spinal units and multi-vertebrae segments. This will provide asystematic quantitative assessment of the determinants of fixation failures. This approach will also enable improving the understanding of the biomechanics of the intervertebral discs and ligaments after different procedures such as facetectomy, instrumentation, etc.

The research team

This candidate will have an engineering background. While this will facilitate him/her in grasping the technical part of the project, some time and effort must be dedicated at the beginning to improve his/her understanding of the clinical problem. This project is rooted between three groups:

– The group of Prof. Cristofolini (Department of Industrial Engineering) will provide “training through research” in the area of biomechanics and material characterization.

– The group of Dr Giovanni Barbanti-Bròdano will provide training and supervision on the surgical procedures for spinal correction, and about the most critical complications.

Dr Barbanti-Bròdano and prof. Cristofolini have been intensively collaborating in the last 5 years on research projects at the intersection between orthopaedic clinical application and biomechanics research, and specifically on spine pathologies. A strong integration of the two research groups has been achieved by involving the clinical staff in lab activity, and the lab staff in clinical research. This PhD candidate will enjoy this extremely stimulating interdisciplinary environment, and will share his/her research time between clinics (in tight collaboration with Rizzoli Orthopaedic Institute) and biomechanics lab.

The Department of Industrial Engineering includes a large Biomechanics lab that is extremely active in the field of orthopaedic biomechanics. The focus of the biomechanics group directed by prof. Cristofolini within

DIN is on the multi-scale biomechanical characterization of skeletal structures and orthopaedic devices, and on the integration of in vitro tests and numerical modeling. Since the beginning (nineties), the focus of this group has been on joint replacement, and in the last decade the group has also been active in the spine area (basic science, osteoporotic fractures, vertebroplasty, fixation). Furthermore, this group is acknowledged internationally for the applications of DIC to biomechanics.

The Complex Structure of Spine Surgery prevalently Oncologic and Degenerative, operating at the Rizzoli Orthopaedic Institute, is a division dedicated to the diagnosis and the treatment of rachis pathologies of oncologic, degenerative and post-traumatic origin. The clinical activity concerns the field of spinal column pathologies: primary and secondary tumors of the mobile rachis and the sacrum, hematopoietic tumors with vertebral localization; degenerative discopathy of the lumbo-sacral rachis, herniated lumbar disc, spondylolisthesis, thoracic-lumbar stenosis, herniated thoracic-rachis disc, pathologies of the cervical rachis; Deformities in adults; Traumatic fractures and insufficiency fractures (osteoporosis). This Complex Structure is the reference center for AOSpine International, a scientific association of vertebral surgeons gathering over 40.000 members worldwide, and favorite destination for all-around specialists for the study and in-depth analysis of the surgical techniquesapplied. The Division participates to the international multicenter Registry for the collection of data on primary tumors of the spinal column (PTRON) and to the international multicenter Registry for the collection of data on metastatic tumors of the spinal column (MTRON), both promoted by the international scientific Association AOSpine Foundation; to the international database for spinal column pathologies “SpineTango”, promoted by the International Association EuroSpine; to the international multicenter study promoted by the Italian Sarcoma Group on the comparison between surgical and radiotherapy treatment of the sacrum chordoma.

The Labs of the Department of Industrial Engineering are equipped with the testing facilities required for this project, including:

– Approved procedures and dedicated space and facilities for safe storage, preparation, testing and disposal of biological tissue specimens (both human and animal)

– Five universal testing machines

– A proprietary multiaxial simulator for biomechanical testing

– Top-of-the-range digital image correlation (DIC) system (4-camera system, up to 100 frames per second). Specific skills useful for this PhD project

The following skills will be considered during the selection: good laboratory practice; mechanical testing and experimental stress analysis; handling and testing of biological tissue; orthopaedic biomechanics; mechanical properties of living tissues; bone biomechanics; soft tissue mechanics; spine biomechanics; in vitro biomechanical testing; experimental stress analysis (digital image correlation); statistics and design of the experiment.

References:

1. Lee, G. A., Betz, R. R., Clements, D. H. & Huss, G. K. Proximal kyphosis after posterior spinal fusion in patients with idiopathic scoliosis. Spine 24, 795–799 (1999).

2. Park et Al. (Spine 29, 17, 2004).

3. Lau, D. et al. Junctional kyphosis and failure after spinal deformity surgery: a systematic review of the literature as a background to classification development. Spine 39, 2093–2102 (2014).

4. Smith, M. W., Annis, P., Lawrence, B. D., Daubs, M. D. & Brodke, D. S. Acute proximal junctional failure in patients with preoperative sagittal imbalance. Spine J. Off. J. North Am. Spine Soc. 15, 2142–2148 (2015).

5. Colangeli S, Barbanti Brodàno G, Gasbarrini A, Bandiera S, Mesfin A, Griffoni C, Boriani S. Polyetheretherketone (PEEK) rods: short-term results in lumbar spine degenerative disease. J Neurosurg Sci. 2015 Jun;59(2):91-6.

6. Yagi, M. et al. Characterization and surgical outcomes of proximal junctional failure in surgically treated patients with adult spinal deformity. Spine 39, E607-614 (2014).

7. Pipola V, Gasbarrini A, Girolami M, Griffoni C, Zaccaro R, Barbanti Bròdano G. Isthmic spondylolisthesis and interspinous process device. Hype, hope, or contraindication? Eur Rev Med Pharmacol Sci. 2019: 2340-44.

8. Barbanti Bròdano G, Lolli F, Martikos K, Gasbarrini A, Bandiera S, Greggi T, Parisini P, Boriani S. Fueling the debate: Are outcomes better after posterior lumbar interbody fusion (PLIF) or after posterolateral fusion (PLF) in adult patients with low-grade adult isthmic spondylolisthesis? Evid Based Spine Care J. 2010 1(1):29-34.

9. Palanca, Ruspi, Cristofolini (2018) “Full-field strain distribution in multivertebra spine segments: An in vitro application of Digital Image Correlation” Medical Engineering & Physics 52: 76-83

10. Palanca, M., Ruspi, M.L., Cristofolini, L., Liebsch, C., Villa, T., Brayda-Bruno, M., Galbusera Fabio, Wilke, H.-J., La Barbera, L., (2020). The strain distribution in the lumbar anterior longitudinal ligament is affected by the loading condition and bony features: an in vitro full-field analysis. PLOS ONE. https://doi.org/10.1371/journal.pone.0227210

PhD project on “Computational modelling of spinal growth and vertebral bone adaptation”

We are currently recruiting a PhD student for a project that was funded by the National Centre for Scientific Research (CNRS), France. The project deals with the development of a computational model to better understand spinal growth and bone adaptation. In particular, the project addresses the question how vertebral bodies grow under normal and pathological loading conditions such as in Adolescent Idiopathic Scoliosis (AIS), i.e. a spinal deformity that leads to abnormal vertebral loading, vertebral wedging and ultimately to a significant deformity of the spine. Furthermore, the altered loads on vertebral bodies may lead to a change in bone mass and re-orientation (i.e., adaptation) of the trabecular bone architecture which could play an important role for the development of osteoporosis at later stages in life. Access to longitudinal MRI data both from healthy and AIS subjects will allow for patient specific modeling of spinal growth and adaptation.

Candidates are expected to have a strong background in continuum mechanics and numerical simulations. A previous experience in a domain related to biomechanics and/or imaging techniques will be an asset.

The PhD project is a collaboration between Prof Vittorio Sansalone, Biomechanics team of the Multiscale Modeling and Simulation lab (CNRS UMR 8208), from the University of Paris Est Créteil (UPEC, France) and Professor Peter Pivonka, Director of Biomechanics and Spine Research Group, from Queensland University of Technology (QUT, Australia). The selected candidate will spend half of the time at UPEC, Paris and half of the time at QUT, Brisbane. The successful completion of PhD studies will lead to doctoral degrees both from the University Paris Est Créteil and Queensland University of Technology.

If you are interested in this position, please send your CV together with a cover letter to either Prof. Vittorio Sansalone (Email: vittorio.sansalone@u-pec.fr) or Prof. Peter Pivonka (peter.pivonka@qut.edu.au) by Friday, May 1, 2020.


PhD position in Computational Mechanics with an emphasis on Biomechanics and Piezoelectric Material

A PhD position shared in collaboration between the Computational Mechanobiology Group at the Julius Wolff Institute (Charite Medical School in Berlin) and the Computational and Structural Mechanics group at the Institute of Mechanics in Technische Universität Berlin is vacant. 

Topic 

Bone has the ability to self-regenerate after injury, however, large bone defects often lead to delayed healing or non-unions. The treatment of these conditions remains a clinical challenge. To overcome the limitations of current bone treatment options, novel alternatives hold promise as the next generation of tissue engineering scaffolds. Experimental trial and error in the design of these scaffolds could be reduced by the development of a computer platform that could support the design of these scaffolds. The project therefore aims to develop suitable numerical models to investigate the behaviour and optimal design of tissue engineering scaffolds and their influence on the bone regeneration process. 

Your tasks 

You will employ engineering, mathematical and computational techniques (FEM) to determine the mechanical and electrical signals generated due to the physiological stimulation of a scaffold and to investigate how these signals influence the bone regeneration process. You will also investigate how different parameters influence the bone healing process. Using this understanding, the potential design optimization of scaffolds (concerning scaffold geometrical and material properties) will be also investigated. You have to be able to employ experimental data available to validate and qualify the numerical prediction. 

Your profile 

 Highly motivated candidate with a Master’s or comparable degree in mechanical engineering/biomedical engineering/material science and engineering/mathematical biology or a related discipline 

 Strong skills in Finite Element Modelling (e.g. Abaqus) 

 Ideally knowledge or experience in material science in particular piezoelectric materials 

 Knowledge in Programming is advantageous (e.g. C/C++, Matlab, Python) 

 Willingness to work in a multidisciplinary project 

 Very good English language skills (oral and written) 

What we provide 

This position is fully funded by the German Research Foundation (DFG) for a period of three years (100%, E13 salary group). You will work in friendly teams of highly qualified researchers and in unique research environments. Expected start date is at the earliest convenience, ideally May 1st, 2020. 

Application / Contact 

Please submit your application before March 31st, 2020 via e-mail to Dr. Melika Mohammadkhah (Melika.mohammadkhah@tu-berlin.de). Your email should contain a single PDF document (subject: “Application: PhD position”) including the letter of motivation, your CV (with contact information of at least two references), transcripts of the bachelor’s and master’s diploma, proof of English language skills. 

14 PhD scholarships within exciting ITN project!

Mediate – The Medical Digital Twin for Aneurysm Prevention and Treatment

https://cordis.europa.eu/project/id/859836/it

MeDiTATe aims to develop state-of-the-art image based medical Digital Twins of cardiovascular districts for a patient specific prevention and treatment of aneurysms. The Individual Research Projects of the 14 ESRs are defined across five research tracks:
(1) High fidelity CAE multi-physics simulation with RBF mesh morphing (FEM, CFD, FSI, inverse FEM)
(2) Real time interaction with the digital twin by Augmented Reality, Haptic Devices and Reduced Order Models
(3) HPC tools, including GPUs, and cloud-based paradigms for fast and automated CAE processing of clinical database
(4) Big Data management for population of patients imaging data and high fidelity CAE twins
(5) Additive Manufacturing of physical mock-up for surgical planning and training to gain a comprehensive Industry 4.0 approach in a clinical scenario (Medicine 4.0)


The work of ESRs, each one hired for two 18 months periods (industry + research) and enrolled in PhD programmes, will be driven by the multi disciplinary and multi-sectoral needs of the research consortium (clinical, academic and industrial) which will offer the expertise of Participants to provide scientific support, secondments and training. Recruited researchers will become active players of a strategic sector of the European medical and simulation industry and will face the industrial and research challenges daily faced by clinical experts, engineering analysts and simulation software technology developers. During their postgraduate studies they will be trained by the whole consortium receiving a flexible and competitive skill-set designed to address a career at the cutting edge of technological innovation in healthcare. The main objective of MeDiTATe is the production of high-level scientists with a strong experience of integration across academic, industrial and clinical areas, able to apply their skills to real life scenarios and capable to introduce advanced and innovative digital twin concepts in the clinic and healthcare sectors.

For application to 12 already available ESR positions please visit:
https://euraxess.ec.europa.eu/site/search?keywords=meditate

Three new fully funded PhD positions in soft biomechanics and medical technologies at the University of Portsmouth

Three fully funded PhD positions are currently available in the field of soft tissue biomechanics and medical technologies at the School of Mechanical and Design Engineering of the University of Portsmouth (UK).

All of the three projects arise from a close and strong collaboration between the research group of Biomechanics and local and national hospitals. They all have a strong drive in clinical practice, from which the underlying research question originates.

The first project is aimed to predict the artero-venus fistula outcome/evolution in patients undergoing hemodialysis; the second project is aimed to provide an in vivo measurement of heart valves deformation; the third project is focused on improving clinical practice for lesion detection and diagnosis in gastroscopy.

Further details about the three projects are available online at:

https://www.findaphd.com/phds/project/in-silico-assessment-tool-for-reducing-the-risk-of-failure-of-arterio-venous-fistula-avf-in-patients-subjected-to-haemodialysis/?p115898

https://www.findaphd.com/phds/project/investigating-the-physiological-deformation-of-heart-valves-using-in-vivo-and-in-vitro-techniques/?p115894

and
https://www.findaphd.com/phds/project/enhanced-endoscopic-screening-of-polyps-in-the-upper-gastrointestinal-tract/?p116271

Brilliant and ambitious students attracted by multidisciplinary subjects, interested in medical applications and strongly oriented to authentic teamworking are invited to apply.

The three positions are opened for UK/EEA applicants.

The deadline for the online application is Friday 23rd 2020. 

PhD in Bath: Multiscale Analysis of the interactions between a Novel Total Artificial Heart and the Native Cardiovascular System

Project Description

Project team: Dr Katharine Fraser (k.h.fraser@bath.ac.uk) & Dr Andrew Cookson (a.n.cookson@bath.ac.uk)

Project
Over 500,000 people in the UK suffer from heart failure, with 14,000 admitted to hospital each year and 10,000 deaths. Worldwide, 26 million have heart failure, with a predicted increase of at least 46 % by 2030. The health expenditure on heart failure in the US alone is $31 billion. For patients with severe end-stage heart failure the only hope of long term survival is a heart transplant. However, donor hearts are scarce, resulting in fewer than 200 heart transplants/year in the UK. Alternative treatments are urgently needed to keep patients alive until a donor heart can be found. One alternative is a Total Artificial Heart (TAH): a machine to completely replace the native heart. Unfortunately, the only TAH on the market suffers from several issues.

Scandinavian Real Heart AB are developing a TAH with a completely novel pumping concept based on displacement of a piston and valve. It is hypothesized that the use of positive displacement, rather than rotation, has major advantages for physiological compatibility. This project will then investigate the interactions between the mechanical device and the native cardiovascular system, with the overall aim of assessing the biocompatibility of the device to aid design optimisation and regulatory approval. Specifically, the aims are to quantify the level of blood damage caused by the TAH, and find the effect of pulse wave it generates on the human arterial system.

The research will involve:
• the use of computational fluid dynamics to simulate blood flow within the Real Heart
• the development of numerical models for damage to the different blood cells
• the use of mathematical modelling to investigate pulse waves in the arteries
There is also the opportunity to perform experimental validation of the numerical results.

Through this PhD the student will become an expert in computational and mathematical modelling of fluid flows, including commercial and opensource software, and in-house code development. By working with Real Heart the student will develop teamwork and communication skills; to strengthen these the student will be based with the company in Sweden for 3 months. The University’s DoctoralSkills training includes a wide range of transferable skills courses. The student will write high impact journal papers and present at leading international conferences. Healthcare technology and biomedical devices are rapidly growing industries; a PhD in this area would equip the student with sought after skills and qualify them for a range of opportunities.

This project is an outstanding opportunity to help bring the next generation of mechanical heart pumps to the clinic. In addition, the research will contribute to fundamental science in incompressible fluid mechanics, blood trauma, and arterial dynamics, and develop new simulation techniques to advance the field of mechanical circulatory support development.

Candidate:
The successful applicant will ideally have graduated (or be due to graduate) with an undergraduate Masters first class degree or very good 2:1 or MSc distinction (or equivalent). English language requirements must be met at the time of application to be considered for funding.

More Details:

https://www.findaphd.com/phds/project/multiscale-analysis-of-the-interactions-between-a-novel-total-artificial-heart-and-the-native-cardiovascular-system/?p110261

Application:
Formal applications should be made via the University of Bath’s online application form for a PhD in Mechanical Engineering. Please ensure that you state the full project title and lead supervisor name on the application form.

https://samis.bath.ac.uk/urd/sits.urd/run/siw_ipp_lgn.login?process=siw_ipp_app&code1=RDUME-FP01&code2=0014

A full application must be submitted by the application deadline, including all supporting documents, to enable review.

More information about applying for a PhD at Bath may be found here:

http://www.bath.ac.uk/guides/how-to-apply-for-doctoral-study/

Anticipated start date: Monday 30 March 2020

Funding Notes

Funding is for up to three and a half years. It includes UK/EU tuition fees, training support fee of £1,000 per annum and a Maintenance stipend of £15,009 per annum (2019/0 rate). EU students are eligible to apply if they have been resident in the UK for 3 years prior to the funding commencing.

Research Assistant in Murnau

 As of April 1, 2020 we are looking for a  Research Assistant (PreDoc, m/f/d)  to strengthen our team at the Institute for Biomechanics  initially limited to 3 years. 

Your duties: 

 Collaboration in the research project “Population variability in orthopaedic bio-mechanics”. The aim is to develop and mechanically characterize materials that serve as synthetic bones for the development and validation of new implants. The methodological focus is on biomechanical testing, medical imaging and finite element analysis. 

 Preparation of and participation in scientific reports and publications 

 Presentation of research results at scientific events at home and abroad 

 Submission of research proposals, participation in externally funded projects 

 Cooperation in teaching and supervision of interns 

Your profile: 

 A completed diploma or master’s degree in biomedical engineering, medical technology, mechanical engineering, civil engineering, technical physics, materials science or equivalent studies in Germany or abroad 

 Craftsmanship and pleasure in manual laboratory work 

 Basic experience in scientific work 

 Programming experience and affinity to statistical analysis methods 

 Strong communication skills and very good knowledge of German and English, both written and spoken 

 Reliability, an independent way of working and pleasure in participating in in-ter-disciplinary teams 

Our offer: 

 A modern working environment with varied activities in a constantly growing clinic with excellent infrastructure and equipment 

 A comprehensive and structured induction training with regulated procedures 

 Further education and development opportunities (e.g. a doctorate at the PMU Salzburg) 

 Support of a work-life balance through flexible working hours and at least 30 days of vacation 

 Attractive remuneration according to TV-BG Kliniken as well as additional social benefits and employee benefits in the region 

The inclusion of people with disabilities corresponds to our self-image and we therefore welcome your application. 

Please send your application with a letter of motivation, curriculum vitae and certificates to the Institute of Biomechanics at the BG Unfallklinik Murnau, Prof.-Küntscher-Str. 8, 82418 Murnau or by e-mail to biomechanik@bgu-murnau.de or via our career portal (www.bgu-murnau.de). We are looking forward to meeting you! 

PhD Position “Machine Learning in Biomechanics”

The ARTORG Center for Biomedical Engineering Research is the University of Bern´s transdisciplinary Center of Excellence for medical technology research. Its mission is to tackle unmet clinical needs and envision future challenge in diagnosis, monitoring and treatment to create viable healthcare technology solutions with imagination, agility and purpose. Its projects run from discovery and basic research to clinical translation. 

The Computational Bioengineering Group has opened a Ph.D. Student position in machine learning to evaluate the risks of failure of total shoulder arthroplasty. You will develop machine learning algorithms to better understand the biomechanics of shoulder replacements and improve patients’ care. You will be part of an inter-disciplinary project funded by the Swiss National Science Foundation (www.snf.ch) performed in collaboration with the Swiss Federal Institute for Technology (www.epfl.ch), and the Lausanne University Hospital (www.chuv.ch). 

You will integrate a research group that develops experimental and computational methods in biomechanics to test original scientific hypotheses, develops new diagnostic methods, and medical devices. 

Your tasks 

– Develop algorithms to analyze medical image and generate patient-specific finite element models 

– Quantify anatomical degeneration of the hard and soft tissues of patients undergoing total shoulder replacement 

– Infer the pre-morbid anatomy of degenerated shoulder joints 

– Determine the optimal treatment strategy from pre-operative data and population-based finite element simulations 

Qualifications required 

– Master’s degree in computer science, engineering, or applied mathematics. 

– Experience and/or course work in computer vision and machine learning 

– Solid programming skills in Python or C/C++/C# 

– Background in mechanics and computational methods 

– Hands-on experience with finite element analysis would be a distinctive asset 

– Strong communication skills in English required (working language at the ARTORG Center) 

We offer 

– Creative and international environment to conduct competitive research in an interdisciplinary team 

– Strong links to the Bern University Hospital (Inselspital) and Lausanne University Hospital (CHUV) to provide a coherent view of how computer modeling in healthcare can benefit patients 

– Competitive salary (according to the guidelines of the Swiss National Science Foundation) 

– Expected starting date; summer 2020 

– Free German courses available for those wishing to learn 

Application Interested candidates should send their detailed resumes with references, motivation letter, abstract of your MSc thesis, and school transcripts to Prof. Philippe Büchler, philippe.buechler@artorg.unibe.ch. 

About the University of Bern The University of Bern is located at the heart of Switzerland. Internationally connected and regionally anchored, it cultivates exchange with society and strengthens partnerships between science, medicine, business, and politics. The University of Bern is committed to a deliberate and ethical responsibility towards people, animate and inanimate nature. As an important educator, promoting enterprise and industry in the region and beyond, it distinguishes itself through problem-oriented research into questions of pressing social relevance. The University of Bern is an equal opportunity employer, promotes healthy work-life-balance and safe working environments, and strives to increase the number of women at all levels in its faculties. 

PhD position at the University of Zaragoza

Position and project

The Biomedical Signal Interpretation and Computational Simulation group at the University of Zaragoza (Spain) seeks a PhD Student to work on the interface between Cardiac Electromechanical Modeling and Artificial Intelligence in the context of ischemic heart disease.

The position is part of the BRAV∃ project funded by Horizon 2020 programme of the European Commission. BRAV∃ aims at providing a lasting functional support to injured hearts through the fabrication of personalized tissue engineering-based biological ventricular assist devices (BioVADs). This ambitious project will combine multimodal deep cardiac phenotyping, advanced computational modeling and biomechanical analysis in a large animal model of disease to create a personalized 3D printable design.

The candidate will work on developing deep-learning neural networks trained on simulated data from large-scale physics-based electromechanical swine models, which is expected to allow obtaining simulated electromechanical data in an efficient way while maintaining accuracy as high as possible. The proposed multidisciplinary approach ultimately aims at contributing to shed light into the interaction between BioVADs and recipient hearts.

Qualifications

Candidates must hold an MSc in Engineering, Mathematics or Physics or similar discipline.

Expertise in computational modeling and/or signal processing is recommended. Strong oral and written communication skills in English are a must. Experience in Python and/or C++ programming is preferred. Previous experience with numerical methods for solving PDEs (e.g. Finite Element Method, Meshless Methods), Artificial Intelligence (e.g., neural networks) and CUDA programming is considered a plus.

The I3A Institute at University of Zaragoza

The Aragon Institute of Engineering Research (I3A), within the University of Zaragoza, comprises more than 500 researchers and a vibrant environment for multidisciplinary research.

Every year I3A participates in more than 300 research projects funded with over 10 M€ and more than 200 contracts with industry with 5 M€ turnover. Around 50 PhD theses supervised by I3A members are defended and nearly 300 papers are published in JCR journals every year. The Biomedical Signal Interpretation and Computational Simulation group at I3A, University of Zaragoza, is a leading expert in the development of signal processing tools to aid in the diagnosis, prognosis and treatment of cardiovascular diseases and conditions. This expertise is combined with modeling and simulation of cardiac electrophysiology to investigate causes and consequences of the phenomena observed from the processed signals.

Application

For additional information about the position, please contact Dr. Esther Pueyo

(epueyo@unizar.es) or Dr. Konstantinos Mountris (kmountris@unizar.es).


Corporate members of the ESB:

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