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or applying machine learning models. Proficiency in programming and data analysis using Python, R, or comparable analytical tools. Demonstrated ability in scientific writing, peer-reviewed publication, and
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 3 hours ago
-adaptive systems. We focus particularly on two properties: self-healing and self-optimization. With self-healing, we aim to study and adapt data mining and machine learning solutions to the design and
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than 18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries. Postdoc: Keystone Project (Machine-Verified LLM Inference) Mission The Keystone project seeks
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leading experts in autism research, computer vision, machine learning, psychiatry, and developmental science to develop innovative technologies that improve how caregiver-child interactions and
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value of these benefits, we have created a tool that calculates the total worth of your compensation package. This tool takes into account all of the benefits that you are eligible for, including health
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related to the project’s objectives. • Process and analyze the collected data by implementing machine learning algorithms and artificial intelligence. • Develop a web-based geospatial interface
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of academic and industry partners, you will help create smart building management tools that improve energy efficiency, occupant comfort, and operational performance. Responsibilities You will develop BIM-based
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, Organometallic, Organic Chemistry and Machine Learning for a period of up to 24 months. The project, funded by EPSRC, will involve exploring the use of machine learning to develop new tools for investigating
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public health. In this role, you will develop and evaluate novel AI and machine learning methods using large-scale multimodal datasets, contributing to epidemiology-informed foundation models, predictive
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characterization (PXRD and Rietveld refinement, SEM, XPS, etc) Experience with machine learning techniques, particularly machine-learned interatomic potentials, in the context of chemical research. Programming