New research positions in the field of in silico medicine opened in the last month with deadlines late March-mid April
PhD position on patient-specific cardiac biomechanics
Cardiovascular mathematics team at Groningen University
Funded by Health Technology Research & Innovation Cluster (HTRIC)
Scientific interests: Personalization of cardiac biomechanics from exercise MRI data
Required background:
Send your CV to Cristóbal Bertoglio c.a.bertoglio@rug.nl by the 16th of April
More info HERE
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Sheffield Children’s Hospital, the NIHR Children and Young People MedTech Cooperative and the Insigneo Institute for In Silico Medicine at the University of Sheffield are recruiting up to 4 PhD studentships in Paediatric Digital Healthcare Technology.
University of Sheffield - Department of Infection, Immunity and Cardiovascular Disease
Supervisors: Professor Jim Wild (representing a team of potential supervisors from Insigneo) and Professor Paul Dimitri (representing a team of potential supervisors from SCH)
Successful applicants will work together in a pioneering cross-disciplinary programme alongside patients, families, clinicians, engineers, computer scientists and other experts to develop new digital platforms and technologies that can address unmet needs in child health. This research will focus on paediatric clinical care pathways and span the Insigneo research themes of Healthcare Data, Artificial Intelligence and Smart Devices and Sensors. It will develop the concepts of Digital Twins, Digital Wards, Digital Healthcare at Home and Advanced Healthcare Communication in paediatric real life healthcare settings with Sheffield Children’s Hospital and in collaboration with Great Ormond Street Hospital.
Closing date: 14 April 2023
More info and application: go to website
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Automatic segmentation of 3D ultrasound for spinal imaging in clinical settings
University of Bath - Department for Health
Dr Dario Cazzola, Prof Neill Campbell, Dr Logan Wade
The overall aim of this project is to enable imaging of the spine via ultrasound. This will be achieved through the following objectives:
More info and application: go to website
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EPSRC Doctoral Training Partnership: A computational biomechanical model to optimise personalised treatments for spine metastases
University of Sheffield, Department of Oncology and Metabolism
Supervisors: Dr Enrico Dall'Ara, Prof D Lacroix
The hypothesis of this study is that SS-FE models can be used to identify the best treatment for reducing the negative effects of vertebral metastases on the bone strength.
The student will learn how to create computational models based on medical images, validate the outputs of the models with state of the art biomechanical data, and apply the models to solve an important clinical problem.
Closing date: 24 March 2023
More info and application: go to website
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PhD Physical Modeling & Simulation
Full time job at Twinical
Twinical is a start-up providing a surgical planning and navigation tool to treat liver cancer patients. We are developing the digital twin of the patient's liver to help the surgeon plan operations virtually and improve his surgical precision by guiding him during the operation. Developed in collaboration with the APHP and more particularly the BOPA innovation chair (www.chaire-bopa.fr) and the Mimesis team from Inria Strasbourg (https://mimesis.inria.fr), our solution reduces the duration of the surgery, improves the postoperative course and reduces the recurrence rate by improving the quality of the resection of tumors not visible with conventional surgical exploration methods.
Integrated within the R&D team, you will work on the main functionality of the company which is the Digital Twin of the organ. You will be in charge of implementing new algorithms in the SOFA framework, to improve this Digital Twin in terms of physical realism while keeping the simulation real time.
More info and application: http://twinical.com/files/Twinical_PhD-Physical-Simulation_JobOffer
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PhD Computer Vision & IA
Full time job at Twinical
Integrated within the R&D team, you will work on computer vision algorithms to be able to process and label the images of the operating room in real time. You will study several image processing algorithms using deep learning to address technical challenges. You will collaborate with researchers, engineers and clinicians on this ambitious project. In more detail, your mission will consist of:
More info and application: http://twinical.com/files/Twinical_PhD-Computer-Vision_JobOffer.pdf
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SOFTWARE ENGINEER (C++/C#)
Full time job at Twinical
Integrated within the R&D team, you will be responsible for the design, development and maintenance of our software for surgeons as well as internal software. In this role, you will work hand in hand with the other R&D engineers to integrate their work into the complete solution. In more detail, your mission will consist of:
More info and application: http://twinical.com/files/Twinical_Software-Engineer_JobOffer.pdf
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FULLY-FUNDED 3.5-YEAR PHD STUDENTSHIP - Developing a deep learning tool for texture analysis of placenta abnormality during pregnancy
University of Sheffield - Department of Mechanical Engineering
Supervisor: Dr Shannon Li
Placenta abnormalities are often responsible for fetal problems such as Intrauterine Growth Restriction (IUGR) or can be inherently abnormal themselves such as Placental Accreta Specturm (PAS). Such abnormalities are increasing as mothers choose to have children later in life and surgical intervention of the uterus continues to increase. These abnormalities are a common cause of both maternal and infant mortality, but the risks can be reduced if diagnosis is received early so that an effective management plan can be put in place. The diagnosis process currently rely on experienced radiologists to examine the scans. We believe this process can be significantly sped up using Deep Learning (DL) algorithms to filter out normal placenta from those that need to be examined further. Recent developments in DL segmentation algorithms have been shown to provide accurate automatic segmentation of various target structures in MRI, such as brain tumor. This project aims to apply such method to automatically segment placenta from patients' MRIs in order to characterise the shape and texture of the structure, so that quantitative data can be provided for differential diagnosis of each mother's condition.
Closing date: 10 March 2023
More info and application: go to website
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Research Associate in Cardiovascular Biomechanics
University of Sheffield - Department of Mechanical Engineering
Supervisor: Dr Alberto Marzo
You will work on the adaptation of existing experimental equipment for the characterization of blood flows within the human cerebral circulation and will support the development and validation of existing simulation tools over a range of HPC platforms to provide efficient simulation tools for end-users from the academic, clinical and industrial sectors.
Closing date: 15th March 2023
More info and application: go to website
