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-VIS-NIR). Experience in hyperspectral data processing (HMSPL, μXRF, μXAS) and statistical analysis (clustering, machine learning) is preferred. Familiarity with fossilization processes and taphonomic
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eligibility. The University offers a comprehensive benefits package that includes: Competitive wages, paid holidays, and generous time off Continuous learning opportunities through professional training and
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photonic quantum sensing and computing. Experience with control electronics, data acquisition systems, machine learning and AI for control and optimization of experimental apparatus. Experience with vacuum
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echocardiography dataset called CAIFE consisting of both healthy and abnormal fetal heart scans. You will be responsible for the design and testing of original machine-learning based methods for fetal heart
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. Representative publication: Midavaine E, Moraes BC, Benitez J, et al. Meningeal regulatory T cells inhibit nociception in female mice. Science 388:96–104 (2025). The lab combines mouse genetics, neuroendocrine
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in privacy preserving machine learning (ML) within the SSF-ML-DH project, under the supervision of Olivier Cappé (CNRS, DI ENS) and Jamal Atif (Ecole Polytechnique, CMAP). Funding is available for two
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trials and deep learning-based modeling of multimodal biomedical data. We are seeking two highly motivated scientists with expertise in Causal Inference / Statistics / Deep Learning / Bioinformatics
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computational backbone. You will then transition to PANDORA, an ARPA-E-funded closed-loop AI platform for catalyst discovery targeting CO2 conversion to fuels and chemicals, where the group leads
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or python, or analytical modeling), OR optomechanics, OR high frequency devices. You are eager to learn and expand your knowledge! Basic knowledge of analog and digital circuits. Experience with various
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learning, optimization, mathematical foundations of artificial intelligence, mathematical ecology and mathematical statistics. Qualifications To qualify as a postdoctoral scholarship holder, the postdoctoral