Two vacancies are available for ambitious individuals to join Maastricht University as part of the ERC STG project “AUTOMATHIC”. This 5-year interdisciplinary project aims to perform cutting-edge research in developing new methodologies for the automated modeling of the dynamic behavior of large biological networks. The project also involves engaging with national and international stakeholders. 

In silico models aim to capture and elucidate the complex and emergent interactions of biological systems, with the goal of expediting research and potential clinical translation. For example, ordinary differential equation (ODE) models of toxin and drug transport are being developed to bring safer therapies to chronic kidney disease patients. Despite recent progress, these cutting-edge ODEs only model transport in steady state and remain limited regarding the amount and complexity of dynamic transport mechanisms as it is often not clear which kinetic relation is most suitable. This limitation is due to the manual and labor-intensive approaches to construct the ODEs, which critically hinder their application in quantitative toxicity assessment in key industrial settings like drug development. In AUTOMATHIC, we aim to develop an integrated framework for automated ODE structure identification, parameter estimation and model evaluation and explore the capabilities of the developed framework for toxin and drug transport in the kidney. 

More information can be found here:

PhD Position: Framework for automated ODE model construction Job Details | Maastricht University

PhD Position: Automated Knowledge Graphs for Kidney Physiology and Pathology Job Details | Maastricht University

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

University of Galway: The University of Galway has world-recognized expertise in biomedical science and engineering, with a particularly strong track-record of developing innovative diagnostic and therapeutic solutions to healthcare challenges. Located in the vibrant cultural city of Galway in the west of Ireland, with over 18,000 students and more than 2,400 staff, the university has a distinguished reputation for teaching and research excellence (https://www.universityofgalway.ie/our-research/). Dr McEvoy is also an investigator at CÚRAM, the Science Foundation Ireland Research Centre for Medical Devices, which is embedded in Galway’s vibrant Med-Tech ecosystem.

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 computational and experimental models for the prediction of patient-specific cancer cell behaviour, to uncover new mechanistic insight and advance multi-scale models. Specifically, the candidate will develop (i) novel microfluidic systems to characterise active cell biomechanics and (ii) coupled predictive models using advanced finite element analysis and agent based modelling. This frontier research will bridge subcellular remodelling and single cell mechanobiology to provide a new fundamental understanding of tumour growth and therapy resistance in breast cancer.

Stipend: Fully-funded four-year scholarship – €22,000 per annum (tax-exempt award). University fees are fully covered by the scholarship. You will also receive a high-end laptop or desktop computer for your research. Travel expenses are included to attend frontier international conferences.

Academic entry requirements: Applicants must hold a Bachelor’s degree in Biomedical or Mechanical Engineering, Applied Maths or a related field. Prospective candidates should be enthusiastic, motivated, and willing to learn new skills.

Start Date: October 2024 – January 2025; the position will remain open until filled.

How to Apply: Interested candidates should send their CV (including the names of two referees) and a one-page cover letter outlining their motivation to work on the project to Dr Eoin McEvoy at eoin.mcevoy@universityofgalway.ie. Please use the email subject line “PhD Application” to ensure that applications are processed. You are also welcome to reach out for an informal discussion on the available projects and positions.

Application Deadline: Applications will be reviewed periodically until September 20^th, 2024.

For more information on moving to Ireland, please see www.euraxess.ie

Applications are invited for a Ph.D. project position within the MAtrix / Mechanobiology & Tissue Engineering research group (www.mech.kuleuven.be/mechanobiology), a bioengineering group that is pioneering the role of cellular forces for microvascular formation and function in health and disease. The group is led by Hans Van Oosterwyck and is one of the few groups worldwide that has established 3D Traction Force Microscopy (TFM) routines and workflows for quantifying cellular force exertion in 3D, and routinely applies them to in vitro models of angiogenesis (endothelial invasion). Together with its research partners, it is currently developing novel in vitro models, compatible with TFM, to study the interplay between cellular force exertion, matrix mechanics and fluid flow, and how this interplay contributes to microvascular lesion formation within the context of specific (genetic) diseases.

Unit website

Project

Cerebral cavernous malformations (CCM) is a microvascular disease characterized by abnormal brain microcapillary beds resulting from mutations in CCM-complex genes, with no current cure. While we have recently demonstrated the significance of aberrant cellular forces for CCM lesion formation in 3D endothelial monoculture systems (see doi: 10.1101/2023.11.27.568780), more complex co-culture systems are needed to better mimic the environment of in vivo lesions. This project centers on deciphering the intricate interactions between endothelial cells (ECs) and pericytes within an advanced vessel-on-a-chip model. By integrating a 3D microfluidic platform with force quantification methods, the study aims to comprehensively elucidate the roles of EC and pericyte forces in CCM progression, emphasizing the dynamic interplay between biochemical and biomechanical factors. Beyond advancing vessel-on-a-chip technology, the project holds promise for broader applications in microvascular disease.

Profile

We are looking for a highly motivated, enthusiastic and communicative researcher with a master’s degree in biomedical engineering, biotechnology or a related field. The candidate should have obtained excellent study results. In addition, we require:

• experience with basic cell culture techniques, optical microscopy, preferably live cell imaging in 3D (confocal microscopy, fluorescence microscopy).
• some experience with or exposure to scientific computing (such as finite element modelling) and programming (such as Matlab).
• a strong interest in mechanobiology and mechanotransduction.
• a collaborative attitude, passion for research, creativity

Offer

We are offering an exciting Ph.D. position in a multidisciplinary, international and collaborative research environment. The MAtrix / Mechanobiology & Tissue Engineering group is working on cutting-edge methods for cellular force inference and is addressing important questions in vascular (mechano)biology in close collaboration with its biomedical partners. The group is based at the Leuven Chem&Tech / Leuven Nanocentre (https://set.kuleuven.be/chemtech_nanocentre) that forms the perfect environment for technology development and that houses unique equipment related to e.g. optical microscopy and nanoscopy, micro-, nano- and biofabrication and biosensing. KU Leuven is one of the oldest universities in Europe, with a very rich tradition in research and higher education. Today, it is among the best 100 universities in the world according to both Times Higher Education World Rankings and QS World University Rankings, and was ranked by Reuters as most innovative university of Europe since 2016. Leuven is a vibrant student town at the heart of Belgium and Europe, offering a great quality of life.

The group works in close collaboration with dr. Eva Faurobert at the Institute for Advanced Biosciences (University of Grenoble, France) and profs. Liz Jones, Aernout Luttun, Rozenn Quark and An Zwijsen (Centre for Molecular and Vascular Biology at KU Leuven), with whom you are expected to closely collaborate as well.

research group website
general information on working conditions
gross salary (salary scale 43)

Interested?

For more information please contact prof. Hans Van Oosterwyck, mail: hans.vanoosterwyck@kuleuven.be, Dr. Jorge Barrasa Fano, mail: jorge.barrasafano@kuleuven.be, Dr. Jyotsana Priyadarshani, mail: jyotsana.priyadarshani@kuleuven.be.

You can apply for this job no later than August 21, 2024 via the online application tool

More information: https://www.kuleuven.be/personeel/jobsite/jobs/60354466?lang=en

We are looking for a motivated and independent PhD candidate to develop highly efficient and robust surrogate models of a multi-scale cardiovascular ‘digital twin’ modelling platform.

A cardiovascular digital twin is a physics-based computer simulation that models an individual’s health and disease states to aid decision-making. These high-fidelity models are often computationally expensive, limiting their personalization and real-time clinical use. In this project, we aim to develop highly efficient data-driven surrogate models for parametrized partial differential equations, with application to computational cardiology.

In this project, you will combine advanced physics-based models of the human heart and vasculature with the latest breakthroughs in machine learning to develop scalable and robust surrogate models of cardiovascular digital twins. These surrogate models will be used to enhance personalized treatment planning and post-treatment monitoring for patients suffering from circulation overload disorders, specifically systemic hypertension, heart failure (with/without preserved ejection fraction), and hemodynamically complicated atrial septal defects.

The research will be conducted in the Department of BioMechanical Engineering at Delft University of Technology (TU Delft) under the supervision of dr. ir. Mathias Peirlinck. The Peirlinck Lab integrates multimodal experimental data, physics-based modeling, and machine learning techniques to understand, explore, and predict the multiscale behavior of the human heart and cardiovascular system. More information on the research and team can be found on https://peirlincklab.com. This research is part of the VITAL project (https://vital-horizoneurope.eu/), a large international collaboration developing a comprehensive, clinically validated, multi-scale, multi-organ ‘digital twin’ modelling platform that is driven by and can represent individual patient data acquired both in the clinic and from wearable technology.

Prior experience in both scientific machine learning and numerical analysis of PDEs and ODEs is required. In addition, experience in the field of cardiac modeling, arterial modeling, (soft tissue) biomechanics, and/or electrophysiology will be strongly appreciated. As the successful candidate for this position, you will develop scientific machine learning algorithms, develop and run high-performance computer simulations, construct pipelines for model personalization to structural and functional data, and develop APIs between various software codes. You will actively participate in (bi)weekly lab meetings, write scientific articles and reports, and give presentations and workshops at national and international conferences. Besides your research activities, you will also take part in teaching and supervision activities within the Faculty of Mechanical Engineering of Delft University of Technology and beyond.

More information:

https://www.tudelft.nl/over-tu-delft/werken-bij-tu-delft/vacatures/details?jobId=17669