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Field
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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 for realistic settings
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. 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 collaborates to address
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Experience with machine learning algorithms and ideally experience developing novel methods Understanding of basic biological principles and experience interpreting ‘omics data Ability to analyse information
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, LiDAR and photonic sensors”. Qualifications For the post of Senior Research Fellow / Senior Project Fellow, applicants should have a doctoral degree plus at least six years of postdoctoral research
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Important: Internal deadline for applications from UZH is 28 April 2025 The number of applications is fixed by the AXA RF to one application per call and institution. Candidates cannot submit directly to the AXA RF, they first have to submit a short proposal to the UZH Research & Grants Office....
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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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team to develop integrated control algorithms for autonomous cubesatellite formation flying. The controllers that will be developed during this project will differ from previous work on this topic by
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algorithmic advances and aim at publishing them at these top venues. More details about the position can be found here. As a KAUST postdoc or researcher, you will have access to state-of-the-art research
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Engineering or equivalent from a recognized University. Major in Power Engineering will be advantageous. Minimum 5 years of relevant experience in power electronics, drives, control algorithms, optimization
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Experience: Knowledge of AI frameworks and algorithms, particularly those related to decision-making and ethical AI. Machine Learning Experience: Knowledge of ML techniques, including reinforcement learning