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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 2 months ago
identify and assess the actual quantitative and qualitative benefits of tailoring software features and behaviors. While changes may be perceived as beneficial by end-users, they may actually create
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proof assistants, into the scientific production workflow Developing a complete and reproducible protocol for mathematical creation, verification, and publication, including formal certification
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experience with existing single-cell methods and software would represent a strong advantage. Excellent communication skills and team spirit, and an ability to work in autonomy are essential. Fluent English
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learning applied to dynamic systems; Proficiency in key machine learning libraries (PyTorch, JAX, etc.); Mastery of Python and the software ecosystem for scientific data analysis and management (NumPy
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for the turbomachinery design optimization process conducted by a parallel PhD student at LMFA. The numerical solver involved is ProLB. It is an innovative Computational Fluid Dynamics (CFD) software solution developed
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of data, services, interaction devices, and use cases influence the evolution of software and systems to guarantee the essential properties such as reliability, performance, autonomy, and adaptability
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Physics, or a related discipline. Experience with recognized computational chemistry software (e.g., Gaussian, Dalton, TurboMole) is highly desirable. Experience in Time-Dependent Density Functional Theory
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software (e.g., Gaussian, Dalton, TurboMole) is highly desirable. Experience in Density Functional Theory (DFT) and Time-Dependent Density Functional Theory (TD-DFT) are desirable assets. Strong analytical
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data scientists, software engineers, biomedical researchers, and clinicians. Your research will focus on developing AI- and LLM-enabled methods and tools to structure, harmonise, and analyse clinical
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of software to validate the integrity and durability of a nuclear power plant containment structure, based on a multiphysics-multiscale approach and data to build a digital twin. • Participate in consortium