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-throughput measurements of molecular binding with simulations and quantitative modeling to gain a physical understanding of life at the molecular level. We are recruiting a Postdoctor that wants to use and
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approaches and research themes here: www.scilifelab.se/researchers/lisandro-milocco/ This project leverages the rise of data-driven dynamic modeling—from fluid dynamics to ecosystem studies—to uncover
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, biophysics Machine learning and generative AI Molecular modeling and molecular dynamics simulations LNP formulation and characterisation including e.g. small angle scattering, microscopy, single particle
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models of interacting ecological and evolutionary (eco-evolutionary) processes. You will conceptualize and model the complexity in which ecological divergence and speciation drive an adaptive radiation
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AI / ML. The unique inter-disciplinary combination will enable: (i) a-priori biological knowledge infusion for GRN modeling and developing GenAI methods for generating GRNs; (ii) generating simulated
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The doctoral student project and the duties of the doctoral student This Data Driven Life Sciences (DDLS) PhD project focuses on probabilistic models of protein structure, which can be used primarily
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study plan. For a doctoral degree, the equivalent of four years of full-time doctoral education is required. The research group Our lab is advancing precision medicine through deep learning models
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by using computational models of development to simulate the evolution of evolvability. Main responsibilities The main tasks include: Large-scale simulations of development and evolution under
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, computational modelling, bioinformatic analysis, and experimental vascular biology. Based in a dynamic translational research environment of data-driven life science, computational imaging, and vascular surgery
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or predictive modelling of pathogen biology or host-microbe systems for which multidimensional, genome-scale experimental data are now available or it may use population-scale genetic, clinical, or public health