PhD Position Scientific Machine Learning and Surrogate Modeling for Cardiovascular Digital Twins

Job title:

PhD Position Scientific Machine Learning and Surrogate Modeling for Cardiovascular Digital Twins

Company:

Job description

Offer DescriptionA 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 . This research is part of the VITAL project ( ), 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.RequirementsSpecific Requirements

• You have demonstrable experience with scientific machine learning and numerical analysis towards solving PDEs and ODEs on complex domains.
• Affinity with nonlinear continuum mechanics, finite element analysis, cardiovascular modeling, computational (soft tissue) biomechanics, cardiovascular (patho)physiology is appreciated.
• You have an excellent master’s degree (or an equivalent university degree) in Computational Physics, Applied Mathematics, Aerospace Engineering, Mechanical Engineering, Applied Physics, Biomedical Engineering or a related field.
• You are a highly independent, motivated, and innovative individual.
• You have a strong research-oriented attitude.
• You are a quick learner, can effectively communicate scientific ideas, and foster collaborations in a highly multidisciplinary team.
• You have excellent spoken and written English* language skills (minimum C1 level).

Please highlight your specific skills and relevant prior experiences for this position explicitly in your motivation letter. Motivation letters that do not address any of these requirements will not be considered.

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the .Additional InformationBenefitsDoctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2770 per month in the first year to € 3539 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.For international applicants, TU Delft has the . This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a for partners and they organise events to expand your (social) network.Selection processAre you interested in this vacancy? Please apply before 15 July 2024 via the application button and upload:

• A 1-2 pages cover letter, explaining in a clear but concise way your motivations to apply to this position and how your CV and expertise fit the requirements.
• Curriculum vitae.
• A copy of your master’s degree, including transcripts for your qualifying degrees (BSc, MSc).
• The contact information of two (academic and/or industrial) referees.
• It is highly recommended to include samples of your work (a digital copy of your MSc thesis, reports, previous publications, videos, code, etc.).

Please note:

• Only complete applications will be considered.
• Screening of applicants will start as soon as applications are received and will continue until the position is filled.
• A pre-employment screening can be part of the selection procedure.
• You can apply online. We will not process applications sent by email and/or post.
• Please do not contact us for unsolicited services.

Additional commentsFor more information about this vacancy please contact Recruitment Services, email: . Website for additional job detailsWork Location(s)Number of offers available 1 Company/Institute Delft University of Technology Country Netherlands City Delft Postal Code 2628 CD Street Mekelweg 2 GeofieldWhere to apply WebsiteContact CityDelft WebsiteStreetMekelweg 2 Postal Code2628 CDSTATUS: EXPIRED

Expected salary

€2770 per month

Location

Delft, Zuid-Holland

Job date

Fri, 31 May 2024 05:51:07 GMT

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