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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 6 days ago
/Qualifications Technical skills and level required : mathematics, programming Languages : English Relational skills : good communication skills Specific Requirements The candidate must hold a PhD in machine
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enterprises (SMEs). The postdoc will work at the intersection of cybersecurity, machine learning, and human centered system design, contributing to the research on privacy aware monitoring, attacker modelling
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neuroscience, and brain-computer interfaces, machine learning and deep learning, statistical modelling, regression methods, and uncertainty quantification, calibration, interlaboratory comparisons, and
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developing cutting edge analytic tools for studying the genome transformation and genomic activities. 70% - The candidate will be mainly focusing on developing machine learning methods and/or AI algorithms
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closely related field Required Qualifications: - Experience in spectral CT and uantitative imaging including radiomics, machine learning, deep learning or artificial intelligence as applied to radiology
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blood samples to advance patient care. This role will involve developing computational models (statistical, machine learning, etc.), and using them to perform high throughput analysis of clinical data
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resonance imaging data among other imaging modalities, machine learning methods for prediction, treatment effect estimation, and contribute to understanding brain biomarkers of Alzheimer’s disease and their
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machine learning methods for detecting, classifying, and identifying wireless anomalies in real-world radio environments. You will design and experiment with AI-driven approaches for spectrum analysis, work
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fellow devotes most of their time to research. There is the possibility of teaching up to 20%. Requirements PhD degree in machine learning, automatic control, system identification, signal processing
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on studying the principles of neural computation through recurrent neural networks, dynamical systems theory, and machine learning. - Develop mathematical and computational models of neural networks - Analyze