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(PhD candidate), COR code 213137, as part of the project titled “Implementation of an advanced protocol for detecting DNA methylation in the blood of colorectal cancer patients: strategic collaboration
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Transformer-Based Foundation Model for DNA Methylation in Longitudinal Cohorts.” The focus is on developing next-generation AI models for the analysis of DNA methylation. Using longitudinal data from, among
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. Investigating epigenetic regulation (DNA methylation, histone modifications) in stem cell fate decisions, reprogramming, and disease modeling using AI predictive tools. Combining computational virtual cell
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proficient in epigenome-related techniques (DNA methylation and/or histone modifications) and their analysis. Alternatively, the candidate comes with an expertise in CRISPR-based epigenetic editing
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cancers (Dentro et al., Cell 2021), the evolutionary history of cancer (Gerstung et al., Nature 2020), biallelic mutations in cancer genomes (Demeulemeester et al., Nature Genetics 2022), combined DNA
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, epigenomics, and proteomics) to simulate virtual neural stem cells or organoids. Investigating epigenetic regulation (DNA methylation, histone modifications) in stem cell fate decisions, reprogramming, and
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epigenetics research in the Cortese Lab. This position is responsible for managing, processing, and analyzing high-throughput sequencing data to support studies of DNA methylation and disease mechanisms
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, analysing DNA modifications (methylation), grant writing are beneficial. Specialised skills will be taught and developed through mentorship and collaborations. Additional information: Salary on appointment
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analyzing DNA methylation data (e.g., preprocessing, normalization, quality assurance). Support basic statistical modeling and data integration activities linking methylation, behavioral, and health outcomes
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, optimizing, and validating procedures for RNA expression analyses; Introducing methods from the field of epigenetics (e.g., DNA methylation); Participating in research investigating: exposure levels