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. Interactions with interdisciplinary teams will be encouraged to integrate biophysical and quantitative approaches. The candidate may also contribute to the supervision of students and trainees involved in
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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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close synergy with partners. Activities: Design and synthesis of photocatalytic materials Development of semiconductor nanoparticles (sensitized or not with grafted dyes) and molecular systems
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thermodynamic and experimental conditions, parametrizing interatomic potentials, and incorporating substrate interactions to align with synthesis scenarios. The researcher will design and execute simulation
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virtual chemical library screening pipeline on a computing cluster (4,000 cores). - Develop protocols for aggregating, processing and filtering the data resulting from the pipeline. - Design an interactive
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of results with project partners - Writing scientific articles to disseminate results to the scientific community - Contributing to interactions with stakeholders on the issue of biosafety and the management
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for nanometric ion implantation based on laser ionization of neutral atoms coupled to a focused ion beam (FIB). The researcher will take part in the design, implementation, and performance characterization
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matter exist in theories beyond the SM, and the WIMP (Weakly Interacting Massive Particle) is one of the best motivated of these candidates, as it allows to also solve the SM hierarchy problem, directly
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(study conducted by our collaborators in Marseille). The postdoctoral researcher will participate in the design, execution, and analysis of behavioral experiments in humans. Furthermore, they will develop
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developing more sustainable catalytic approaches. Special attention will be given to overcoming identified limitations through the design of new catalytic systems based on abundant and non-critical transition