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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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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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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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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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, 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
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methods in applied mathematics and computational modeling, this specific project aims to uncover new insights into how blood cells form in both healthy and disease states. A key objective is to model
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microtumor models. This work addresses a critical knowledge gap in cancer immunobiology and supports the development of more accurate disease models. Duties The main duty for a doctoral student is to devote
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vision, machine learning, deep learning and neural networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid