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department in the ISSA expertise center that develops advanced AI solutions involving AI models, algorithms, implementations, sensors and hardware for small scale edge up to large scale distributed and hybrid
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advanced machine learning models and physics-informed algorithms for analyzing high-speed XRD data, with a focus on identifying critical transformation windows and assessing phase evolution kinetics
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At the Fraunhofer Institute for Laser Technology ILT, we may not be developing lightsabers to fight the dark side of the force, but our innovationsoften sound like something out of science fiction
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Federated learning (FL) is an emerging machine learning paradium to enable distributed clients (e.g., mobile devices) to jointly train a machine learning model without pooling their raw data into a
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Student (f/m/d) in Quantum Algorithms for Droplet and Bubble Oscillation Dynamics Modelling. Your tasks Development and implementation of numerical and algorithmic methods for the simulation of fluid
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available in the further tabs (e.g. “Application requirements”). Programme Description The research and training programme focusses on the mathematical and algorithmic foundations of reliable AI along with
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algorithm to reduce noise in dual-tracer PET imaging and improve the quantitative accuracy of dual-tracer PET scans. Your Job Simulation of PET data using existing simulation packages. Development
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will help to develop advanced, real-time atmospheric turbulence correction algorithms to enhance the long-range imaging quality of optical sighting systems. You will embed new knowledge
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clinical trials, cancer genetics, immunology, epigenetics, machine learning, statistical software development, Bayesian methods, and alignment algorithms. Roles and Responsibilities Conducts research as an
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SHARE@NTU Lab is developing key technologies for humanoid robot research, designed for intelligent service, industrial assistance, and human-centric environments. The key technologies include