14 physics-engineer "https:" "https:" Postgraduate positions at Forschungszentrum Jülich
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information about our institute here: https://www.fz-juelich.de/en/ias/ias-8 Your Job: Develop physics-aware simulations of growing cell populations, including their spatiotemporal manipulation in microfluidic
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, 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
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information about our institute here: https://www.fz-juelich.de/en/ias/ias-8 Your Job: Develop 3D+t image reconstruction methods in a cell microscopy setting using image sequences as well as focus stacks
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, energy systems, or material sciences A Masters degree with a strong academic background in mathematics, computer science, physics, material science, earth science, life science, engineering, or a related
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into the open-source CADET simulation framework, enabling fully predictive process simulations without extensive experimental calibration. Embedded in the Helmholtz Graduate School for Data Science in Life, Earth
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international conferences Supervise student theses Your Profile: Excellent Master`s degree with a strong academic background in computational engineering, mathematics, computer science, physics, engineering or a
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computational engineering, mathematics, computer science, physics, engineering or a related field Strong background in numerical methods and machine learning Proficiency in at least one programming language
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Your Job: We are looking for a PhD student to contribute to the development of fast, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular
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a project linked to the “Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE)”. Your Job: Develop physics-aware simulations of growing cell populations, including their spatiotemporal
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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