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) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global
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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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, generative AI, and molecular modeling, the student will contribute to creating faster, more accurate predictive tools. The student will work closely with Dr. Filip Miljković (Associate Principal AI Scientist
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, such as molecular data (e.g. omics), imaging, electronic health care records, longitudinal patient and population registries and biobanks. To be a doctoral student means to devote oneself to a research
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. The long-term goal is to enable targeted interventions for the right individuals, based on their lifestyle, disease trajectories, and molecular profiles. To achieve this, we will apply deep learning models
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molecular mechanisms that drive its invasive behavior, both general and patient-specific. Using cutting-edge spatial techniques and CRISPR-based methods, we build data-driven models that link gene regulation
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welcome you to apply for a DDLS PhD position in Data-driven cell and molecular biology at the Department of Information Technology, Uppsala University. The Department of Information Technology holds a
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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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of cancer cells. The models are trained on high-throughput datasets, including metabolomics, proteomics, and transcriptomics, and constrained to align with the cell’s molecular networks. This allows us to
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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