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Field
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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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an opportunity for a Postdoctoral Fellow. You will contribute to UNSW’s research efforts in developing machine learning and deep learning algorithms for dynamic systems (sequential or time-series data). Experience
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. Key Responsibilities: Develop safe-learning algorithms for embodied intelligence of robots. Integrate LLMs and safe-learning into unmanned vehicle platforms using ROS or similar systems. Collaborate
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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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research initiatives that analyze the impact of AI technologies on social systems and design innovative methods for adapting economic and social governance to AI development. A special focus will be
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developing and devising machine learning algorithms in an energy context Ability to assess research resource requirements, and use resources effectively, to plan and manage research activity Strong analytical
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. Experimentation & Implementation - Develop and implement the related algorithms, models, and techniques. - Perform rigorous benchmarking and evaluation of the developed models. - Optimize algorithms for efficiency
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Processing and Machine Learning to develop signal processing and machine learning algorithms and methods for communication networks. Key Responsibilities: Develop signal processing and machine learning
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HiPerBreedSim project. In this role, you will leverage recent advances in working with ancestral recombination graphs (ARGs) to develop algorithms and code for simulating population genomic data, including
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tools. This insight opens the door for enjoying the real world. The candidate further develops efficient and robust algorithms for realistic settings in terms of data and computing resources and