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SD-26085 POSTDOCTORAL RESEARCHER IN THE OXIDATIVE CHEMICAL VAPOR DEPOSITION OF FUNCTIONAL BUILDIN...
, including innovations in all that we do · An environment encouraging curiosity, innovation and entrepreneurship in all areas · Personalized learning programme to foster our staff’s soft and
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technologies (fiber-optic sensors, DIC), and computer science (machine learning tools) in collaboration with de department of Physics. The aim of the BriCE project is to develop a novel bridge monitoring
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. In this project, we aim to develop digital tools combining density functional theory (DFT) and machine learning (ML) to accelerate the in-silico design of solid catalysts for the DA process. - Perform
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-learning models for patient stratification and outcome prediction. Moreover, complex multi-layered datasets shall be integrated into clinically actionable biomarkers and decision-support tools that underpin
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of the protocol and acquisition sequences on a 7T MRI You are autonomous and endowed with learning and creative abilities You like working in a team and are comfortable communicating with technical and non
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molecular dynamics simulations of modified nucleosomes - analyze the large data set obtained using various analysis tools, from visualization to automation using machine learning tools - perform QM/MM
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these autonomy and self-adaptation capabilities. Three major challenges have been identified: (P1) modelling uncertain environments where robust, weakly supervised machine learning algorithms can be deployed
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the project team, you will ensure the simulation of drone missions using state-of-the-art tools for AI learning and demonstration. You will be responsible for producing training data for vision models and
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Description CNRS offers a 18-month fixed-term contract researcher position to work on the recently funded project ACCTS (“Assessing cirrus cloud thinning strategies by learning from aerosol-cirrus interactions
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conferences. • Contribute to the writing of scientific publications. Optional : • Design Machine Learning (ML) potentials. • Code in FORTRAN and PYTHON to improve the functionality of the global