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team as a PhD candidate to work on beyond the state-of-the-art model distillation and robustness methods, enabling efficient, reliable inference for challenging real-world problems in the semiconductor
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%). You will work at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research will primarily focus on probabilistic methods for data-driven model
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-based models, within an active and collaborative research environment. Website for additional job details https://blogs.upm.es/gthau/luis-fernando-dharo/ Work Location(s) Number of offers
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mechanisms governing their catalytic activity remain poorly understood. Their structural heterogeneity and chemical complexity make accurate atomistic modeling particularly challenging.[1] Recent advances in
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problems are highly valued. Familiarity with statistical modeling, data mining, and pipeline development for genomics and neurodevelopmental research will enhance a candidate’s profile. The appointee is
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pipelines that push technological boundaries for our clients. The Engineer will tackle complex challenges at the intersection of Large Language Models, Computer Vision, and Predictive Analytics while ensuring
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correction and disease modelling organoid systems, to join our world-class research team at the Frazer Institute to support and drive dermatology research. This position builds on our recent foundational work
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model organisms in their work and are pushing into emerging model and non-model organisms that are proving uniquely valuable in particular studies. To learn more about our department, https
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skills in Matlab and/or Python, R C2 Experience with collection and analysis of EEG and/or fMRI data C3 Experience with Drift Diffusion and/or Reinforcement Learning models C4. Research creativity and
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The Energy Systems Analysis Group (https://acee.princeton.edu/research/energy-systems-analysis-group/) at the Andlinger Center for Energy and the Environment invites applications for postdoctoral