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Description We are recruiting a contract researcher to join a project involving the development of predictive models for simulating material forming processes, within the mechanical engineering department
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modelling. MISSION You will actively contribute to the development and evaluation of new hybrid computational method to predict biological tissue deformation with subject-specific material properties
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the flexibility and power of NNs with the ability of LMMs to robustly learn from structured and noisy (non i.i.d.) data, applying them on the prediction of both plants and human phenotypes. These models will
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:this project pioneers a new paradigm of General Genome Interpretation (GenGI) models by combining DNA Large Language Models (DLLMs) with Deep Neural Networks to predict human phenotypes directly from Whole Exome
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responsibility of developing predictive tools based on machine learning for the analysis and interpretation of Raman vibrational spectra applied to battery materials. The successful candidate will design and
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entanglement. - Theoretical and Analytical Studies: Conduct theoretical and numerical analyses of superradiant molecular ensemble models, with thorough documentation of processes and results. - Simulation Code
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prediction of gene perturbation effects for drug discovery. The successful candidate will play a leading role in developing gene perturbation models that combine foundation models (FMs) and graph neural
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. Measuring and predicting the effect of copy number variants on general intelligence in community-based samples. JAMA Psychiatry 2018 75(5):447-457. –Bourgeron T. From the genetic architecture to synaptic
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methods to integrate transcriptional and cellular dynamics. Analyze large-scale transcriptomic and spatial dynamics datasets. Work in close collaboration with the team's biologists to test predictions from
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data to compare gene expression profiles between diploid and polyploid individuals. The goal is to determine whether polyploidization disrupts dosage compensation, as predicted by Orr, and to interpret