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with physics-informed neural networks, automatic differentiation, neural ODEs, or other physics-aware DL techniques. Skill in programming languages such as Python, C/C++, Go, Rust etc. Ability to model
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methods (LBM). For fluid simulations, we utilize the high-performance LBM framework waLBerla, predominantly written in C++, but increasingly adapted for GPU computations through automatic code generation
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regular arrays to probe novel quantum phenomena in strongly interacting quantum systems. The use of molecules is motivated by their rich internal structure, combined with the existence of controllable long
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control. Successful candidates should have knowledge in one or more of the following areas: Responsibilities: Environmental microbiology for microbial community analysis, antibiotic-resistant genes and
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non-standard register layouts and memory-mapped peripherals (accelerators), ena-bling automatic recognition of customized debugging symbols (example in DARE: AIPU). • Low-Overhead Instrumentation
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Council through project 2024-04957 “Compiling General-size Linear Algebra Expressions using Equality Graphs”. The postdoctoral researcher will be part of the High-Performance and Automatic Computing group
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innovative testbeds to revolutionise smart grid research and 6G communications. The group is equipped with an extensive array of resources: · UAVs for communication protocol, edge computing and control
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in literature review methodologies, and have a good command of research knowledge relevant to Contextual Safeguarding. Research experience, including from their PhD, is essential, however we are open
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management strategies for tomato grafting using diverse pools of rootstocks and scions Conduct research under controlled environment and protected cultivation systems (growth chambers, greenhouse hydroponics
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C++, capable of performing high-fidelity, differentiable attitude and orbit control simulations of spacecraft and their environment. This new system will be user-friendly, portable and easily