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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 4 days ago
: 265566 Vacancy ID: PDS003971 Position Summary/Description: The Miao Lab in the Computational Medicine Program and Department of Pharmacology at the University of North Carolina – Chapel Hill (https
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10 Apr 2026 Job Information Organisation/Company Gustave Roussy / Inserm Department U981 / Molecular Predictors and New Targets in Oncology Research Field Medical sciences » Cancer research
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Department Summary The Department of Molecular, Cell, and Developmental Biology advances our knowledge of life on earth at the cellular and molecular levels. Our mission is to educate the next
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for digital twin: 3D model learning, prediction models from imaging and molecular data, model-based simulation coupling, and uncertainty-aware outputs for lab/clinical validation. Work with 3D datasets, time
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. In vitro approaches include mammalian cell culture, molecular biology, microscopy, immunohistochemistry, functional genomics, proteomics, high throughput drug screening, and genome-wide sequencing. In
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research focuses on identification of tumor cell of origin and elucidating the role of tumor microenvironment in cancer development. We dissect the cellular and molecular mechanisms of carcinogenesis from a
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, including approaches based on immunotherapy and oncolytic viruses; development and application of advanced experimental models, including 3D cultures, organoids, and in vivo models; integration of multi-omic
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molecular modelling methods, including molecular mechanics, molecular dynamics and quantum mechanics. Practical experience with small-molecule binding affinity prediction, e.g. MM/PBSA and free
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differential equation models of bacterial persistence. A particular challenge, both for simulation and for machine learning, lies in the high dimensionality of these equations, which causes grid-based numerical
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animal models of psychiatric diseases, behavioral experiments in mice, and in basic cellular and/or molecular biology techniques, Knowledge of neural mechanisms of learning, memory, and/or other aspects