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Field
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statistical and computational methods motivated by potential applications to observational studies. The work will involve both methodological research with biostatistics faculty and collaboration with clinical
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to exploit some of the cutting-edge experimental and computational methods, comprising constraint-based and kinetic modeling, statistical analysis of large datasets, high-throughput metabolomics, time-lapse
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analytical methods and digital capability for data consumption, organization, validation, storage, and classification of electronic health data. Job Duties Develops analytical methods and digital capability
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of neurodegeneration. Practical experience with C90rf72 genetic models in Drosophila. Preferred Qualifications: Use of Gal4 and Gal80 methods in Drosophila. Q-RT-PCR. Brief Description of Duties: | The Postdoctoral
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will work closely with Drs. Audrey Hendricks and Ryan Layer as well as grad students, postdocs, and other collaborators to develop and implement statistical and machine learning methods, software
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(model-based) systems engineering, whilst applying systems analysis techniques based on formal methods, AI, and optimisation and will be expected to submit publications to top-tier conferences and journals
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terrestrial or flying vehicles and robots Expertise State estimation of floating base robots Relevant background on environment reconstruction, semantic segmentation and classification Expertise on obstacle
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18 Nov 2025 Job Information Organisation/Company UNIVERSITE DE TECHNOLOGIE DE COMPIEGNE Department Department of Computer Engineering Research Field Engineering » Control engineering Researcher
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control (MPC) under uncertainty for autonomous systems. The research aims to develop state-of-the-art numerical methods for solving challenging belief-space optimal motion planning problems and their
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collaborates with faculty, students, and external partners to translate rigorous methods into practical tools. QUALIFICATIONS: Ph.D. in Applied Mathematics, Electrical & Computer Engineering, Computer