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The successful candidate will develop computational approaches to discover, model, and develop therapeutic strategies. Examples of potential approaches include: -Network Modeling: Creating
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available to work on computational models of artificial evolution for aptamer design, expected to start between November 2025 and February 2026. Aptamers are often obtained through rounds of in vitro
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of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024, pp. 3184–3194. [4] Y. Zeng, X. Zhang, H. Li, J. Wang, J. Zhang, and W. Zhou, “X 2-vlm: All-in-one pretrained model for vision
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observed in Drosophila larvae. This interdisciplinary project combines biology, neuroscience, and computational modelling to understand how the larva’s body’s physical properties influence its motor control
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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Methods in Computer Vision, 2023. [4] S. Y, J. Sohl-Dickstein, D. Kingma, A. Kumar, S. Ermon, and B. Poole, “Score-based generative modeling through stochastic differential equations,” 2021. [5] H. Chung, J
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rank models [Sportisse et al., 2020], random forests [Stekhoven and Buhlmann, 2012] or deep learning techniques with variational autoencoders [Mattei and Frellsen, 2019, Ipsen et al., 2021]. One
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involving mouse models of Alzheimer’s disease, immune cell phenotyping, and brain tissue analysis. Responsibilities: Assist in the design and execution of in vivo experiments using mouse models. Perform flow
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) models. Little attention has been paid to other models like graph NNs (GNNs) or PCA. Among the few existing works in the literature, [2] proposes an FL algorithm to compute PCA in a DP fashion, but the
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within a coherent computational model is currently challenging, due to the typical large dimension and complexity of biomedical data, and the relative low sample size available in typical clinical studies