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Field
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include but are not limited to: network architecture design for NTN and terrestrial network (TN) convergence, intelligent traffic steering algorithms between TN and NTN, orchestration of TN/NTN resources
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, the appointed candidate will work closely with the line manager to develop novel control algorithms in EAP soft robotics combining Gaussian Predictors, hands-on laboratory experiments and JULIA computing
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technologies, ethical implications, and governance frameworks, including knowledge of algorithmic accountability and transparency. Experience with both qualitative and quantitative research methods, and
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Condensed Matter Physics and Materials Sciences o Theoretical and Computational Biophysics o Soft Matter Physics o Physical Chemistry and Theoretical Chemistry o Combinatorics, Algorithm, Extremal Graph
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or use existing simulation platforms to validate the developed algorithms and models. Analyse simulation data, and create visualizations to support research findings. Design and build prototypes
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, Algorithm, Extremal Graph Theory, Computing Theory o Programming Language, AI Theory or Machine Learning o Classical and Quantum Algorithm for Computational Quantum Many-body Theory o Theory and Computation
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information of the data to make a prediction using advanced mathematical tools. This insight opens the door for enjoying the real world. The candidate further develops efficient and robust algorithms
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mathematical modelling tools. Excellent knowledge of programming languages such as R, Python, Julia, etc. Familiarity with AI algorithms and Machine Learning Fluent oral and written communication skills in
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develops efficient and robust algorithms for realistic settings in terms of data and computing resources and collaborates to address major challenges in important applications including marine domain and
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Abrahao (NYU Shanghai) and João Sedoc (NYU Stern). Research Focus Areas Our research encompasses topics in DL and AI, including but not limited to: Deep Learning Algorithms and Paradigms Generative Models