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Field
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-aware learning methods with domain decomposition techniques, enabling parallel training and efficient GPU-supported implementation. Your tasks: Development of physics-aware ML models for 3D blood-flow
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, cyber-physical systems, real-time systems, autonomous systems, middleware, parallel computing, operating systems, Edge AI or AI in cyber-physical systems; Demonstrate strong analytical, programming, and
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-phase chemistry coupled with solid-phase reaction clean up using tethered reagents that enable pure compounds to be screened without further purification. These methods will allow the parallel synthesis
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screened without further cumbersome purification. These methods will allow the parallel synthesis and testing of ca. 100 compounds in a single operation, potentially taking less than a week to design
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Your tasks: Developing optimization algorithms for massively parallel hardware architectures such as AI
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Declaration of interest regarding PhD project within the field of biomarker and therapeutic targe...
. The PhD student will work with patient cohort to perform biomarker analyses and statistical modeling of clinical outcomes. In parallel, the student will contribute to the development and validation of novel
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Start Date: Between 1 August 2026 and 1 July 2027 Introduction: This PhD is aligned with an exciting new multi-centre research programme on parallel mesh generation for advancing cutting-edge high