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single mirror image forms is often denoted as “A Signature of Life”. Homochirality is essential for, e.g., molecular recognition and information processing, enzyme functioning and cell replication. However
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PhD candidate fascinated by human embryonic development? And do you believe in the power of embryo models and single-cell omics approaches to unravel how human embryos cope with genetically abnormal
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PhD position - Modelling the emergence of information transfer in prebiotic self-replicating systems
and inheritance. Using an open-ended model, we will explore molecular structures of life as we know it (DNA), as well as other potential polymerisation rules. These models will also help interpret and
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on the biology and the regulation of protein lipidation. You uncover the role of the writers and erasers through molecular biology techniques combined with proteomics mass spectrometry. PhD position 2 is focused
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modelling of materials and machine learning. Experience in atomistic modelling (molecular dynamics, density functional theory) and machine learning is important, as well as a strong interest in pursuing
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Engineering, Computational Physics, Materials Science or a related discipline is required, with experience in atomistic modelling of materials and machine learning. Experience in atomistic modelling (molecular
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regulation of protein lipidation. You uncover the role of the writers and erasers through molecular biology techniques combined with proteomics mass spectrometry. PhD position 2 is focused on the development
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approaches, you will establish accelerated Design-Build-Test-Learn cycles to continuously improve models via active learning and guide evolutionary trajectories toward promising but otherwise inaccessible
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medicine. As a PhD student, you will: Build computational models that integrate molecular and genetic data to study possible OA treatments. Develop bioinformatics pipelines, network-based approaches
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the gap between advanced machine learning and clinical application. Your tasks are: - Exploring molecular dynamics and proteomics methods to enhance variant interpretation, which may also include a role for