PhD Position in Digital Twins: Join our team at Delft University of Technology to develop highly efficient and robust surrogate models of multi-scale cardiovascular ‘digital twins’. These models will revolutionize personalized treatment planning for circulation overload disorders. Apply by July 15, 2024.
PhD Position in Scientific Machine Learning and Surrogate Modeling for Cardiovascular Digital Twins
Summary Table:
- Designation: PhD Candidate
- Research Area: Scientific Machine Learning, Surrogate Modeling, Computational Cardiology
- Location: Department of BioMechanical Engineering, Delft University of Technology, Netherlands
- Eligibility/Qualification: Master’s degree in Computational Physics, Applied Mathematics, Aerospace Engineering, Mechanical Engineering, Applied Physics, Biomedical Engineering, or related field. Prior experience in scientific machine learning and numerical analysis required.
- Job Description: Develop efficient surrogate models for parametrized partial differential equations in cardiovascular digital twins. Conduct research under the supervision of dr. ir. Mathias Peirlinck. Participate in teaching and supervision activities within the Faculty of Mechanical Engineering.
- How to Apply: Submit a cover letter, CV, copy of master’s degree, contact information of referees, and samples of work via the online application button before July 15, 2024.
- Last Date for Apply: July 15, 2024
Designation: PhD Candidate
Research Area: Scientific Machine Learning, Surrogate Modeling, Computational Cardiology
Location: Department of BioMechanical Engineering, Delft University of Technology, Netherlands
Eligibility/Qualification:
- Master’s degree in Computational Physics, Applied Mathematics, Aerospace Engineering, Mechanical Engineering, Applied Physics, Biomedical Engineering, or related field.
- Prior experience in 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.
- Excellent English language skills (minimum C1 level).
Job Description:
Develop efficient surrogate models for parametrized partial differential equations in cardiovascular digital twins. Conduct research under the supervision of dr. ir. Mathias Peirlinck. Participate in teaching and supervision activities within the Faculty of Mechanical Engineering.
How to Apply:
Interested candidates should apply before July 15, 2024, by submitting:
- A 1-2 page cover letter
- Curriculum vitae
- Copy of master’s degree, including transcripts for qualifying degrees (BSc, MSc)
- Contact information of two referees (academic and/or industrial)
- Samples of work (digital copy of MSc thesis, reports, previous publications, videos, code, etc.)
Please apply online via the application button. Incomplete applications will not be considered.
Last Date for Apply: July 15, 2024
