-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
on computer vision, image processing, or machine learning Solid mathematical and physics background, distinct analytical skills Very good programming (Python, C++) and computer (Linux, Windows) skills
-
, computer 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
-
Infrastructure? No Offer Description Work group: JSC - Jülich Supercomputing Centre Area of research: PHD Thesis Job description: Your Job: We are looking for a PhD student to contribute to the development of fast