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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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, 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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, helping to shape future research infrastructure Present your results on conferences in Germany and abroad Your Profile: Excellent Master’s degree in statistics, physics, mathematics, or a related
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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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results Your Profile: A Masters degree with a strong academic background in physics, mathematics, computer science, or a related field Proficiency in at least one programming language (Python, C
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. Your Profile: A Masters degreee with a strong academic background in physics, mathematics, computer science, or a related field Proficiency in at least one programming language (Python, C
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disciplines (meteorology, environmental science, high performance computing, software development and data science). Your Profile: Mandatory qualifications are: M. Sc. degree in meteorology, physics
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physics-aware simulations of growing cell populations, including their spatiotemporal manipulation in microfluidic environments Design and implement reinforcement learning algorithms for control and
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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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, computer science or mathematics (or a related field), with a focus on computer vision, image processing, or machine learning Solid mathematical and physics background, distinct analytical skills Very good