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the commercialisation of all-solid-state batteries. Of particular interest is the development of electro-chemo-mechanical phase field models to predict void evolution and dendrite growth (see, e.g., doi.org/10.1016
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and other cancers, as well as their microenvironment, especially immune effectors. The researcher will use a broad range of approaches (genetic, cell biological and in vivo modeling) to understand how
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. The central challenge in our field has been the failure of preclinical models to predict clinical efficacy, a problem we address by conceptually reframing the disease. We operate from the hypothesis
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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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, and conducting large-scale quantitative analyses of semantic change. You will work closely with Latin linguists to integrate linguistic insights into computational models and help build open-source
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The Theory and Modeling Group at the Center for Nanoscale Materials (CNM), Argonne National Laboratory (near Chicago, Illinois), invites applications for a postdoctoral appointment focused on theory
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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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Challenge project “Preparing for a new world of weather and climate extremes,” a project which is co-lead by the Howland Lab and will join a collaborative group of Postdoctoral, PhD, SM, MEng, and
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the commercialisation of all-solid-state batteries. Of particular interest is the development of electro-chemo-mechanical phase field models to predict void evolution and dendrite growth (see, e.g., doi.org/10.1016
-
, and conducting large-scale quantitative analyses of semantic change. You will work closely with Latin linguists to integrate linguistic insights into computational models and help build open-source