New calls with deadlines end May-early June
Research Associate in Preclinical Musculoskeletal Imaging and Biomechanics
School of Medicine and Population Health - University of Sheffield
This highly interdisciplinary Research Associate position will advance our understanding of the effect of biomechanical and pharmacological treatments for Osteoporosis (OP) in a mouse model. The position is within Insigneo and is funded as part of a project selected by the ERC-Consolidator and funded by the EPSRC that aims to develop and validate new multiscale computational models for optimising treatments for OP. This part of the project is focused on the collection of experimental and imaging data to inform and validate the models.
The successful candidate will develop microCT and microMRI in vivo imaging approaches to measure longitudinally the properties of bones and muscles in mice. They will also establish a mouse gait laboratory for the 3D longitudinal assessment of movement in mice. These approaches will be used to measure the effect of Osteoporosis and related treatment on the musculoskeletal health and mobility and to inform and validate computational models of bone adaptation developed within the team.
Deadline: 4 June 2024
More info and application HERE
_________________________________________Research Associate
Faculty of Health - School of Medicine and Population Health -
Are you interested in developing the first Virtual Mouse Twin for the optimisation of treatments for Osteoporosis?
This highly interdisciplinary Research Associate position will advance our understanding of the effect of the combined biomechanical and pharmacological treatments on musculoskeletal biomechanics using mouse models, personalised multibody dynamics models, and subject specific finite element models.
The position is within Insigneo and is funded as part of a project selected by the ERC-Consolidator and funded by the EPSRC that aims to develop and validate new multiscale computational models for optimising treatments for OP. This part of the project is focused on the development and integration of personalised multibody dynamics models of the mouse hindlimb and finite element models of the mouse tibia. These models will be the basis for the virtual mouse twin, that will be used to test new interventions against Osteoporosis in silico.
Deadline: 4 June 2024
More info and application HERE
_________________________________________Research Technician
Division of Clinical Medicine - School of Medicine and Population Health - University of Sheffield
You will join the SkeletAl laboratory with experts of bone imaging and analyses, helping local, national and international customers to obtain the most accurate research results. You will work in a well-connected team of technicians and academics with world-leading reputations in characterising bone from different analyses (imaging, histology, biomechanics, etc.). Take a look at our website for more details: http://skeletal.group.shef.ac.uk/! In this varied and dynamic role, you will be responsible for maintaining and developing procedures for imaging at high resolution different materials and training customers to use our machines. Working alongside laboratory members with different skills, the role will offer you an opportunity to learn about several lab techniques.
You will join also the group of Prof. Enrico Dall’Ara. Our biomechano-imaging group has an international and interdisciplinary profile and a strong commitment to clinical and industrial translation with impact in future healthcare. We are active in imaging and biomechanics of the skeletal systems and we have access to different experimental, imaging and computational facilities.
Deadline: 4 June 2024
More info and application HERE
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Phd Position in Multiscale Modelling of Endothelial Cell Monolayers in Health and Disease
Computational Science Lab, University of Amsterdam, Prof. Alfons Hoekstra
PhD position focusing on multiscale modelling of Endothelial Cell (EC) monolayers in the microvasculature, coupling molecular models of intracellular signalling to cell-level models of spatially resolved signalling, and finally to coupling many of such single cell-level models together in a multicellular EC monolayer. The goal is to study specific pathways (based on RhoA and RhoB GTPases) and their impact on EC monolayer integrity. You will study differential pathways that drive fast and transient (RhoA-mediated), or slow and persistent (RhoB-mediated) loss of endothelial integrity. You will merge in silico modelling with in-vitro experiments carried out in close collaboration with another PhD student in this joint project to address bistability and hysteresis in the differential RhoA/B-dependent control of microvascular leak. You will study cell-to-cell variability in responses to activating stimuli and address the switch from acute to chronic EC activation.
Application deadline: 10 June 2024
More info and application HERE
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A biochemo-mechano multi-scale computational model to predict bone adaptation over space and time
University of Sheffield - School of Medicine and Population Health
Musculoskeletal diseases as osteoporosis have huge impact on the mortality and morbidity of our ageing society. At the moment there are some pharmacological interventions for treating osteoporosis but they are not effective in all patients and their cost is very high. New interventions have to be tested in animal models before clinical studies, the mouse being one of the most used models.
The Finite Element approach based on biomedical images can be used to estimate accurately how bone deforms under external loads.
The project aims at developing the first multi-scale biomechanical model for the prediction of bone changes over time in the mouse tibia due to external biomechanical and biochemical stimuli, and at validating its outcomes versus state-of-the-art longitudinal micro-computed tomography (microCT) measurements of bone adaptation.
Deadline for application: 10 June 2024
More info and application HERE
_________________________________________Postdoctoral Researcher Position at Wearable Robotic Systems Lab
Stevens Institute of Technology (Hoboken, NJ), with a secondary appointment at Columbia University Irving Medical Center (New York, NY)
This four-year project leverages real-world gait monitoring technology (instrumented insoles developed by the project team) and advanced machine learning models to identify digital mobility outcomes (DMOs) reflecting symptomatic severity in progressive neuromuscular disorders and evaluate the DMOs’ ability to predict disease progression longitudinally, in terms of ambulatory function.
The postdoctoral researcher will lead the development of the next-generation AI-Sole, AI-enabled instrumented insoles for stride-by-stride spatiotemporal and kinetic gait monitoring in natural environments. They will apply supervised machine learning models to identify spatiotemporal and kinetic DMOs reflecting walking function and evaluate their clinimetric properties. Additionally, they will collaborate with clinical partners, participate in project meetings, publish research findings in high-impact journals, present at conferences, supervise graduate students, and contribute to grant writing.
Qualifications: Candidates should have a Ph.D. in Mechanical, Biomedical, Electrical Engineering, Computer Science, or a related field. They must have a strong background in machine learning, signal processing, and wearable sensor technologies, with experience in gait analysis and digital biomarkers preferred. Proficiency in MATLAB (required) and Python (preferred), excellent communication skills, a track record of peer-reviewed publications, and a strong work ethic and time management skills are essential.
Application: Send a cover letter (limited to one page), CV or Resume, and contact information for three professional references to damiano.zanotto@stevens.edu. One-year term initially, with the possibility of extension based on performance.
Apply by June 15, 2024
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PhD Student Position at Wearable Robotic Systems Lab
Stevens Institute of Technology (Hoboken, NJ)
The PhD student will assist the research team in the development, fabrication, and validation of the next-generation AI-Sole. They will analyze wearable sensor data collected from healthy controls and individuals with neuromuscular disorders. Additionally, they will gain experience in developing and applying machine learning models to real-world gait data, conduct comprehensive literature reviews, lead the preparation of manuscripts for publication, and present research findings at academic conferences and lab meetings. The PhD student is also expected to participate in project meetings and interdisciplinary collaborations within the research team.
Qualifications: Candidates should have a Bachelor's or Master's degree in Mechanical, Biomedical, Electrical Engineering, Computer Science, or a related field. They must have a strong interest in wearable technology, machine learning, and digital health. Programming skills in MATLAB (required) and Python (preferred), excellent problem-solving skills, attention to detail, strong written and verbal communication skills, a strong work ethic and time management skills, and the ability to work independently and collaboratively are essential.
Application: Submit your CV, transcripts, and a cover letter (limited to one page) describing your research interests and career goals to damiano.zanotto@stevens.edu
Apply by June 15, 2024
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PhD on Digital Twin in Healthcare for Brain Perfusion and Metabolism
Computational Science Lab at the University of Amsterdam
Project: Digital Twin in Healthcare for Brain Perfusion and Metabolism
Aim: Building upon earlier computational models for brain perfusion, metabolism, and infarction, you will develop a high-fidelity Digital Twin, that will become a generic modelling and simulation platform to study (patho)physiology of brain perfusion and related processes (metabolism, infarction, oedema, bleeding in the brain, vasospasm, etc.). The Digital Twin will be validated against clinical data, and credibility assessments will be performed. Finally, in collaboration with (clinical) partners, the Digital Twin will be applied to contribute to decision support tools in preventing or treating strokes.
Context: The research is part of Gemini project (https://dth-gemini.eu), a large international collaboration developing and applying Digital Twin in Healthcare for ischemic and haemorrhagic strokes. In your research you will be collaborating intensively with a number of partners in this project.
Deadline for application: 17 June 2024
More info and application HERE
_________________________________________PhD position Biomechanics of internal fixation methods for ankle fusion
University of Sheffield - Department of Mechanical Engineering
Ankle fusion is a common treatment for advanced ankle arthritis to relieve pain and improve functional outcomes. However, there is a reported non-union rate of 5-37%, requiring further surgery or an ankle replacement. Moreover, there are several options for internal fixation, with no consensus on the number of screws, orientations, and placement in ankle fusion surgery.
This project aims to develop validated computational models of the foot and ankle, and investigate the biomechanical parameters impacting successful bone healing while reducing the risk of fixation failure.
The project will involve parametric analysis of participants’ data, finite element analysis and mechanical testing. Hence, the candidate will be consulting with collaborators in orthopaedic surgery, bioengineering, mechanical engineering and the Insigneo Institute. The candidate will gain a unique opportunity to carry out research in an exciting interdisciplinary project to answer important clinical questions.
Deadline for application: 18 June 2024
More info and application HERE
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Efficient In Silico Trials for Bone Diseases
University of Sheffield - Department of Mechanical Engineering
The School of Mechanical, Aerospace and Civil Engineering at the University of Sheffield is recruiting for a PhD position associated with the EPSRC funded New Investigator Award BONESFE. The position will be based within the Integrated Musculo-Skeletal Biomechanics Group in the Insigneo Institute for in silico Medicine, a collaboration between the University of Sheffield, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield Children's NHS Foundation Trust and Doncaster and Bassetlaw Teaching Hospitals NHS Foundation Trust.
With a focus on bone diseases and drugs and devices used to treat them, the project will leverage recent advances in the characterisation of bone shape variation in a population and in the development of intrusive stochastic finite-element analysis tools. The overall aim of the project is to improve the efficiency and reduce the cost of conducing In Silico Trials, thus encouraging uptake of this technology by device and drug manufacturers.
Deadline for application: 28 June 2024
More info and application HERE
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PHD POSITION ON CARDIORESPIRATORY MODELLING AND SIMULATION IN CRITICAL CARE
Cardiovascular & Respiratory Physiology (CRPH) group of the University of Twente
In this 4-year project you will use computational modelling and simulations to create clinical decision support tools that will ultimately improve the daily care for critically ill patients. The focus of this ground-breaking research is on better understanding of heart-lung interactions and possible applications in acute and critical care (anaesthesiology and intensive care). In this project, 0-D computational models of the cardiovascular and respiratory systems including mechanical support will be used to optimize diagnostic and therapeutic solutions.
Deadline for application: 30 June 2024
More info and application HERE
