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) for life science research projects are important to understand the computational methods. Extensive (3+ years) experience of applying and/or developing advanced digital image analysis methods in the field
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collaborators and strong access to compute through national GPU systems (NAISS, e.g. Berzelius and Arrhenius) and local GPU infrastructure. Project description The position offers significant scientific freedom
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experiment at CERN. Together, the groups offer an international environment with a wide network of collaborators, generous support for conference travel, and access to national HPC resources (NAISS) and local
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cell-cell interactions to disrupt cancer-promoting equilibria. We aim to develop in silico and in vitro models and tools to build and validate digital twins of such interactions, with the objective
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methods are developed in parallel, the postdoc will develop systems and services that make biological data accessible to AI and computational tools, collaborating closely with the Human Protein Atlas (HPA
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accessibility and flexibility across thousands of proteins under native conditions. These experimental data will be used to guide, train, and benchmark machine-learning models that predict protein conformational
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opportunities for international exchanges. You will be employed on a doctoral studentship which means that you receive a contractual salary. Employees also have access to our modern gym for free and receive
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education. Research collaboration involves disseminating, making accessible, and creating value from research findings. The position entails close interaction with leaders and experts from various
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Ouyang’s AICell Lab at KTH and SciLifeLab, and the Human Protein Atlas , and has access to state-of-the-art computational infrastructure, including the Berzelius supercomputer. Your mission The emphasis
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approximately 60 doctoral students. The department offers a strong research environment with unique opportunities for synergy and collaboration between theoretical and experimental activities. Access to BSL2 and