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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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Your Job: This PhD project bridges between classical analytical methods and modern AI based techniques to analyse spike train recordings to advance our understanding of neural population coding while maintaining clarity in the interpretation of results. Concurrently, AI-based methods are...
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1-year fellowship in Shoebill Conservation Genetics with support for a further 3-year PhD fellowship
genetics) and work in the lab. In parallel, you would write a PhD fellowship application to the Swiss Government Excellence Fellowship with support from African Parks, University of Basel, Copperbelt
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of complex behaviours such as void formation and brittleness. In parallel, you will explore formulation and processing strategies to improve toughness, reduce embodied energy and eliminate the need for cold
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the development of solutions for parallel processing, information systems, computer networks, cluster and cloud computing, among others. 3- Good communication skills, as their tasks will include user support
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develop a digital twin of the PFA cure process, combining mechanistic modelling with neural‑network‑based prediction of complex behaviours such as void formation and brittleness. In parallel, you will
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between chemistry and biochemistry. It is structured around two parallel PhD projects: one in chemistry (the position offered) and one in biochemistry, supervised by partner research team. This organization
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-field code, written in the Cuda C language and parallelized on a single GPU (Graphical Processor Unit). A parallelization on multiple GPUs would be a welcome development during the thesis. Where to apply
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in areas including life cycle assessment, farm systems modelling, economic analysis, and sustainability assessment. In parallel, the candidate will undertake professional development activities
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efficiency Optical neuromorphic computing is emerging as a promising alternative to classical electronic architectures, offering advantages in terms of speed, energy consumption, and parallelism. Nonlinear