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science, or mathematics (or a related field), with a focus on robot vision and control, image processing, or machine learning Solid mathematical and physics background, distinct analytical skills Very good programming
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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
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computer vision methods and their applications Your Profile: Excellent Master’s degree in engineering, computer science or mathematics (or a related field), with a focus on computer vision, image processing
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for applications for PhD positions. The Leibniz Graduate School on Aging (LGSA) belongs to the Leibniz Association - a non-university research organization equivalent to the Max Planck Society and the Helmholtz
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Your Job: This PhD project develops a Bayesian inference framework for hybrid model- and data-driven modeling of metabolism, with a particular focus on handling model misspecification. By combining
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to domain-specific knowledge and research. All three domains – life & medical sciences, earth sciences, and energy systems/materials – are characterized by the generation of huge heterogeneously structured
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Do students receive financial aid? All doctoral positions are fully funded, including social benefits. Students also receive funding to attend conferences and other events related to their research, and have access to outstanding facilities. Do I need to know English? Yes, English is the...
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descriptors, molecular simulations, and machine learning, this PhD project seeks to predict ion-exchange isotherm parameters directly from molecular properties. These predictions will be integrated
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international conferences Prepare 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
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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