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, control theory, or a related field. Strong statistical understanding and a talent for data analysis and visualization using Matlab or Python are expected. Specific experience with experimental design
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. Strong foundation in at least one of the following areas: Adaptive control theory Guidance and path planning Machine learning for control or estimation Excellent communication skills and a demonstrated
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efficiently. c) Integrate planning and control algorithms with differentiable simulation technologies to build a trajectory data collection system that generates high-quality, diverse task data for vision
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of fidelity measures. Play a key role in contributing health psychology expertise (theory and methods) to the development and roll-out of a randomised controlled trial and mixed methods evaluation. Identify
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. We have recently developed cross-eukaryotic theory linking this motion to the essential maintenance and sharing of biomolecules across the cellular population of mitochondria (PMID 38043948). Already
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of current issues and future directions within the field of Active Inference, control theory or Bayesian inference. B7 Experience with building computational models of human users in an interaction setting. B8
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society. The reasons for this behaviour remain poorly understood, and outside of some model species, this behaviour itself is poorly characterised. We have recently developed cross-eukaryotic theory linking
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adaptive trials, stepped wedge trials and cluster trials. You will have good knowledge of applied statistics and statistical theory, especially for pragmatic trials and complex randomisation systems. You
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for the position will be ranked based on: A solid background, and any relevant research experience or high-quality publications, in robotics, machine learning, control theory, autonomous systems and mathematics
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mine to magnet. What You Will Do: Use and develop minerals and materials databases for computed and measured properties. Predict and control mineral reaction pathways using first-principles