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Field
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machine learning for safe and optimal control of cyber-physical systems. The projects are expected to be funded by the VILLUM INVESTIGATOR project S4OS (“Scalable analysis and synthesis of safe, secure and
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the development of specialized hardware architectures capable of efficient, real-time processing. Embedded AI hardware architectures, including neuromorphic processors and low-power AI accelerators
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- and Q-band EPR spectrometer. The candidate will be responsible for designing, building, and optimizing instrumentation and methods to investigate complex catalytic systems — including both synthetic and
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Optimized Design and Control of Soft Aerial Manipulators), in collaboration with INRIA Lille Nord-Europe in France and its leading Defrost team in soft robot simulation and control, see https
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/ Robust) Combinatorial Optimization, Game Theory, and Network Theory, as well as Artificial Intelligence. Potentially, scenarios could be simulated using agent-based, discrete-event, or other techniques
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) to optimize the production of bio-based products in E. coli and other industrially relevant bacteria. You can find more information about our group at https://www.linkmetabolism.com . Your tasks: Design and
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research lines. Research line 1: "Digital twinning for 3D network optimization" focuses on developing distributed digital twin architectures and mechanisms for distributed network optimization in networks
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@rmit.edu.au Please send your CV to akram.hourani@rmit.edu.au Required Skills: Programming and simulation: strong experience in Python or MATLAB. Mathematical modelling: probability, optimization, or multi-agent
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Optimizing a 3D microfluidic IVD model to study cell responses to wear particles, refining culture conditions, and analysing cytotoxic and inflammatory mechanisms. Optimizing a 3D microfluidic IVD
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to tackle real-world agricultural challenges. Information about the research group and the IPB can be found on the homepage: www.ipb-halle.de . To ensure optimal training in the diverse skills required