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DC-26094– POSTDOC/DATA SCIENTIST – AI-DRIVEN CLIMATE RISK MODELLING AND EARLY WARNING SYSTEMS FOR...
abiotic resources. We integrate remotely sensed information with in-situ data, process-based models, and leverage satellite communication, IoT and machine learning technologies in order to provide evidence
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complex biological systems. Research Environment & Collaboration The successful candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 2 days ago
to intertwine a multi-contact whole-body controller, a digital simulation of the interacting humans, and machine learning models to predict and respond to human movements and intentions. In a crescendo of
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profile and an interest in developing new AI models for high-dimensional biological data. You should have a solid foundation in areas such as machine learning, applied mathematics, statistics
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/359354/2-phd-positions-on-learning-cau… Requirements Additional Information Website for additional job details https://www.academictransfer.com/359354/ Work Location(s) Number of offers available2Company
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analysis Background in biomedicine and digital pathology What we offer Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within
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to sustain an active research and publication agenda and to teach in the departmental undergraduate and graduate programs. Candidates with expertise in machine learning, big data, mathematical finance and
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integrated onto drone platforms engineered by project partners, with the objective of assessing the structural integrity of concrete façades. Objectives The objective of this PhD thesis is to develop a Machine
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next-generation machine learning (ML) models that are both data-efficient and transferable, enabling more reliable catastrophic risk prediction, defined as the probability of exceeding critical safety
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engineering or similar. Knowledge and experience with deep learning models applied in computer vision. Remarkable academic trajectory, validated by a strong record of publications in relevant international