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, signal processing, sensor fusion, machine learning, and data-driven modeling, with the broader goal of advancing human-centered intelligent infrastructure, smart cities, and resilient communities
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machine learning or computer vision, or be in the final stage of their PhD with a scheduled or imminent thesis defense. A strong publication record is required. We are looking for candidates who have
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circuit models and algorithms for estimating the charge, health, and power based on direct methods (e.g. open circuit voltage), model-based methods (e.g. Kalman filtering), data driven methods (e.g. machine
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skills, including generalized linear models, multiple machine‑learning algorithms, MOFA and multi‑omics pathway analysis. · Strong background in experimental design, quantitative data analysis, and
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of engagement. Read more at: Department of Computing Science Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven
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to staff position within a Research Infrastructure? No Offer Description Activities: The post-doctoral researcher will develop machine learning models to evaluate the effectiveness and cost
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experience in statistical modelling and/or machine learning for regression or distribution estimation, and in time-series or signal processing; proficiency in Python. Advantage: Hands-on field or experimental
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chain, ranging from synthesis, cell assembly, characterization, modeling to scaled-up manufacturing. The 2-year postdoctoral project Machine Learning-based Electro-Chemo-Mechanical Estimation and Control
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/recruitment/2-year-postdoctoral-p… ** Project ** Computational and high field MRI characterization of learning and decision-making ** Supervisor and contact ** Dr Florent MEYNIEL https://www.unicog.org/lab
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field Demonstrated expertise in one or more of the following areas: Machine/deep learning, artificial intelligence, statistical modeling, or computational modeling Human neuroimaging analysis, including