24 phd-in-architecture-interior-design-built-environment Postgraduate positions in Germany
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the areas of Architecture, Interior Design, Monument Conservation and Building in Existing Contexts/Reconditioning of Old Buildings, Urban Planning/Urban Development, Landscape Architecture, Landscape
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environments Design and implement reinforcement learning algorithms for control and manipulation, first in simulation and later on real experimental setups Refine a real-time planning and execution architecture
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course of study in the fields of Fine Art, Design, Visual Communication and Film. The scholarships also promote the exchange of experience and networking amongst colleagues. Who can apply? You can apply if
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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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approaches across a range of model organisms to understand how and why we age. As a PhD candidate at FLI, you’ll be part of an international and interdisciplinary environment where basic science meets
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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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Your Job: The Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE) provides an interdisciplinary environment for educating the next generation of data scientists in close contact
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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
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instances to solve new, yet similar, instances more efficiently than with general purpose algorithms such as Netwon`s method. In particular, we aim to develop a neural network architecture that will allow us
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type, developmental stage, treatment) to build tissue- and context-specific co-regulation networks Design and implement clustering and integration approaches (e.g., network-based and subspace clustering