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Field
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implement VLA models and world models. Develop and optimize deep learning algorithms to enable robotic arms to perform complex tasks guided by natural language instructions. Utilize PyTorch to train and fine
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localization algorithms, spearhead energy-aware navigation planning systems development, and oversee real world validation of underwater navigation technologies while mentoring junior team members. Key
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mathematical or computational algorithms. Strong scientific programming skills. Evidence of the ability to conduct research independently and to identify and address challenging research questions. Evidence of
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learning, generative AI or LLM-based systems, cloud computing, and the design and validation of algorithms for high-volume quantitative or sensor-derived data. Experience with wearable data, health
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Localization and Perception System based on Multi-sensor Fusion Job Description: Responsible for development of robust and reliable sensor fusion algorithms for localization and navigation algorithms of robot in
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learning-based model predictive control (MPC) algorithms for multi-agent multirotor drone navigation around vessels in maritime environments. The role will focus on integrating multirotor crash predictions
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practices Contribute as a co-author to interdisciplinary peer-reviewed manuscripts, with primary responsibility, as appropriate, for computational, algorithmic, and data-methodology sections Contribute
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Dunedin and will be supervised by Associate Professor Colin Fox. The successful applicant will play a leading role in developing scalable Bayesian algorithms, probabilistic models, and computational methods
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ideas from machine learning, econometric choice modelling and mathematical psychology. You will investigate how large language models, optimisation algorithms and automated model search methods can
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knowledge of agentic AI/AI workflows, parallel computing, algorithms, and system performance analysis and optimization. Proficiency in programming languages such as C/C++ and Python. Demonstrated ability