PhD position - Predicting the stress field in atherosclerotic plaque of arteries using scientific machine learning within the HDS-LEE graduate school
PhD position - Predicting the stress field in atherosclerotic plaque of arteries using scientific machine learning within the HDS-LEE graduate school
PhD position - Predicting the stress field in atherosclerotic plaque of arteries using scientific machine learning within the HDS-LEE graduate school
PhD position - Predicting the stress field in atherosclerotic plaque of arteries using scientific machine learning within the HDS-LEE graduate school
Forschungszentrum Jülich GmbH
Erziehung, Bildung, Wissenschaft
Jülich
- Art der Beschäftigung: Vollzeit
- 58.500 € – 75.000 € (von XING geschätzt)
- Hybrid
- Zu den Ersten gehören
PhD position - Predicting the stress field in atherosclerotic plaque of arteries using scientific machine learning within the HDS-LEE graduate school
Über diesen Job
We are offering a
PhD position - Predicting the stress field in atherosclerotic plaque of arteries using scientific machine learning within the HDS-LEE graduate school
Information on the application process and an overview of FAQs can be found here
Your Job:
We are looking for a PhD student to develop learning-based surrogate models for predicting stress fields in patient-specific arteries. Especially high stresses in plaque can lead to rupture, which is one cause of a stroke and thus the prediction of plaque rupture is very relevant. The steps in the development of surrogate models are building data-driven models from medical imaging, extending them with physics-based approaches, and adapting existing physics-integrated neural network approaches for stress prediction in arterial walls and plaque. Another part of the project is exploring the use of large language models to support neural network design and data preprocessing. The position involves close collaboration with experts in cardiovascular simulation and Scientific Machine Learning.
Your tasks:
- Development and comparison of data driven models for the prediction of stresses in arterial walls and plaque
- Enhancing the models with physics, i.e., using different physics-aware machine learning models from the field of scientific machine learning
- Exploiting large language models to support neural network design and data preprocessing
- Participation in conferences in Germany and abroad (incl. presenting your research results)
- Preparing scientific publications and project reports
Your Profile:
- Genuine interest in data science and one or more of its application domains: life and medical sciences, earth sciences, energy systems, or material sciences
- University degree (M.Sc. or equivalent) in applied mathematics or in computational engineering science, computer science, simulation science with a strong background in applied mathematics
- Excellent programming skills (Python, C/C++)
- Good experience in machine learning and parallel computing
- Good organisational skills and ability to work both independently and collaboratively
- Experience with deep learning frameworks, such as Tensorflow or Pytorch is advantageous
- Effective communication skills and an interest in contributing to a highly international and interdisciplinary team
- Working proficiency in English for daily communication and professional contexts (TOEFL or equivalent or excemption required)
- Knowledge of German is beneficial
Our Offer:
We work on the very latest issues that impact our society and are offering you the chance to actively help in shaping the change! We offer ideal conditions for you to complete your doctoral degree:
- Outstanding scientific and technical infrastructure
- Highly motivated groups as well as an international and interdisciplinary working environment at one of Europe’s largest research establishments
- Continuous scientific mentoring by your scientific advisors
- Chance of participating in (international) conferences
- Unique HDS-LEE graduate school program (including data science courses, soft skill courses and annual retreats) https://www.hds-lee.de/about/
- A qualification that is highly welcome in industry
- 30 days of annual leave and flexible working arrangements, including partial remote work
- Further development of your personal strengths, e.g. via a comprehensive training program; a structured program of continuing education and networking opportunities specifically for doctoral researchers via JuDocS, the Jülich Center for Doctoral Researchers and Supervisors: https://www.fz-juelich.de/judocs
- Targeted services for international employees, e.g. through our International Advisory Service
The position is limited to three years, with a possible one-year extension. Pay is in line with 75% of pay group 13 of the Collective Agreement for the Public Service (TVöD-Bund) and additionally 60 % of a monthly salary as special payment ("Christmas bonus"). The monthly salaries in euro can be found on the BMI website: https://go.fzj.de/bmi.tvoed.entgelt
Further information on doctoral degrees at Forschungszentrum Jülich (including its various branch offices) is available at https://www.fz-juelich.de/en/careers/phd
We welcome applications from people with diverse backgrounds, e.g. in terms of age, gender, disability, sexual orientation / identity, and social, ethnic and religious origin. A diverse and inclusive working environment with equal opportunities in which everyone can realize their potential is important to us.
The following links provide further information on diversity and equal opportunities: https://go.fzj.de/equality and on specific support options for women: https://go.fzj.de/womens-job-journey
We look forward to receiving your application. The job will be advertised until the position has been successfully filled. You should therefore submit your application as soon as possible.
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