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preclinical in vivo animal models? Then this position might be perfect for you! Join us! We are looking for a highly qualified and motivated PhD candidate to conduct research activities aimed at unravelling
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performance utilizing reliable and computationally efficient numerical structural models. To support the condition (state) assessment, you will also explore the use of advanced estimators (e.g., Kalman Filter
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of the nonlinear structural performance utilizing reliable and computationally efficient numerical structural models. To support the condition (state) assessment, you will also explore the use of advanced estimators
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within the broad topics of modelling tool-workpiece interaction in mechanical material removal processes, zero-defect manufacturing, machining system performance characterization as well as on-machine and
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Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience-informed design
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development. The successful candidate will contribute to the development of deep learning methods to predict reaction outcomes and optimal reaction conditions for organic reactions. The work will involve model
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depression and the role of the endocannabinoid system? Do you enjoy working in a lab with preclinical in vivo animal models? Then this position might be perfect for you! Join us! We are looking for a highly
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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | 8 days ago
of DMA buffers). Identifying common unsafe patterns or assumptions in the use of kernel APIs. Exploring tools (e.g., static analysis, symbolic execution, model checking, formal specification) to verify
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with process safety and security concepts, accident modelling approach, and dynamic Bayesian Networks would be advantageous. Willingness to conduct research in a multi-national project team. Fluent in
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. Familiarity with software for protein–ligand interaction modeling 5. Ability to carry out multi-step chemical syntheses of organic compounds, confirmed by prior experience (e.g., during master's thesis work) 6