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Field
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functional assays will be used to test and refine model predictions. As a successful candidate you will: · Develop and apply computational models of adaptive oncogenesis, epithelial cell
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simulations, microwave power deposition, tissue perfusion, and bioheat transfer. Perform mesh-convergence, sensitivity, uncertainty, and model-verification analyses. Compare computational predictions with
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damage-tolerant structural alloys for extreme environments. The role will integrate AI, computational mechanics and experimental data to predict deformation and fracture behaviour and guide
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computational model routines and developing reliable coupling interfaces rather than relying only on external preprocessing or file-based exchange Demonstrated experience developing or modifying model
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(e.g., electrophysiology), as well as optimally leveraging integration with existing genomics datasets. The role is focused on computational analysis and supporting model development as part of a
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, artificial intelligence and computational humanities. The exact research questions will be refined together with the successful candidate. Relevant methodological directions include language model
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well as practical experience in dynamic model development and the analysis of large-scale biological data, who are excited to apply rigorous computational modelling approaches to real biological and
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datasets. - novel algorithms & computational approaches, based on maths, statistics, & machine learning, to nominate novel cancer therapeutic targets. - innovative, molecularly engineered model systems in
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through cutting-edge research. The Nath Lab is seeking highly motivated applicants for a postdoctoral position in computational oncology, artificial intelligence, and data science. Our research program
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Systems Location Moscow Posting Context Statement Develops alternative futures and resilience pathways by translating model outputs into spatial and temporal scenarios for a regional testbed. Applies