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algorithms. Strong programming skills in Python and/or R. Experience in analyzing both quantitative and qualitative research data. Experience in statistical consulting, dashboard development, and data
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interplanetary travel. Autonomous Systems: Develop AI algorithms, robotics, and autonomous software to enhance spacecraft operations and exploration. Implement machine learning techniques for improved autonomy and
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exploration. Data Science and Analysis: Develop algorithms and tools for data processing, modeling, simulations, and analytics to support scientific research and mission planning. Spacecraft Operations: Oversee
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for aircraft and spacecraft. Develop and enhance avionics components and systems, including integrating avionics with guidance, navigation, and control (GN&C) algorithms. Focus on advancing autonomous flight
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the appointment, and will have experience in asymptotic, algorithmic or probabilistic combinatorics, or a closely-related area. Applicants should also be active researchers with good written and oral
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Applied Machine Learning: Knowledge of integrating machine learning models and algorithms into applications. • A knowledge of applied computer science and AI in software/app development and rapid prototype
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clinical trials. This includes the design of a data model, building and testing projects within the data model and end-user testing. Some projects may also require algorithms or other calculations be built
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learning models, including their strengths, deficiencies, and strategies for (hyper)parameter optimization. Prior use of Bayesian optimization or other relevant active learning algorithms is preferred
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scientific questions or develop algorithms that perform automatically some challenging tasks. This typically involves exchanging actively with collaborators and domain experts to understand the precise
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. By integrating cutting-edge multi-agent systems, federated learning, and game theory, this project will develop sophisticated decentralised algorithms that enable autonomous vehicles (AVs