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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The project is a follow-on to a project conducted at CAMS on modeling the spread
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combines multimodal neuroimaging with computational modeling to characterize the neural mechanisms underlying human social decision making. The focus of this project will be to unravel the neurocomputational
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: PhD in engineering or related field, with post-doctoral research experience in flow and transport in porous media. - Know-how: Mathematical modeling, micro/milli-fluidic experimentation - Soft skills
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Profile First Stage Researcher (R1) Positions PhD Positions Country France Application Deadline 12 Dec 2025 - 20:00 (Europe/Paris) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer
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Post-doctoral Researcher in Multimodal Foundation Models for Brain Cancer & Neuro-degenerative Disea
Qualifications PhD in machine learning, computer vision or a related field. Established expertise in deep learning methods applied to images analysis. Experiences with generative models, volumetric image
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translational projects in a dynamic and supportive research group, leveraging advanced models and state-of-the-art technologies. Where to apply E-mail broggi@ciml.univ-mrs.fr Requirements Research FieldBiological
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 4 days ago
latent spaces). Integrate dynamic, geometric, and biophysical features extracted from large MD simulations. Train and benchmark models on state-of-the-art datasets. Collaborate with PhD and Master students
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simulations (integrated modelling) can be used to better understand the dependencies obtained in scaling laws and better constrain them beyond the existing experimental space. This is the goal of the present
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. They will collaborate closely with the PI and the PhD students of the team, interact with international partners, and participate in the supervision and coordination of Master's interns involved in
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Information Eligibility criteria The candidate must hold a PhD in physics, chemistry, or materials science. Skills in theoretical modeling (ab initio, DF(P)T, GW) will be appreciated. The candidate will work in