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and efficiency. Key Responsibilities: Develop and implement novel machine learning algorithms for protein sequence annotation. Design and train encoder-decoder language models tailored to protein
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their differentiation, using epimutations and single cell DNA methylation readouts (see biorxiv preprint ). The student will further develop the application of this method to human blood- ansd bone marrow samples and in
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Higher Education System (minimum 300 ECTS) or equivalent by October 2024Strong background in protein research Experience in characterizing proteins with biophysical methods Experience with bioinformatic
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discipling within the European Higher Education System (minimum 300 ECTS) or equivalent by October 2024 You are fluent in English Desirable but not required/ Nice to have Computational Biology Skills
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on mutation influx and in how we can identify cancer driver events from observed mutation data. To this end, we develop mathematical and computational approaches to estimate mutation rates, tumor growth
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data. To this end, we develop mathematical and computational approaches to estimate mutation rates, tumor growth dynamics and selection. Analysis of the mutational processes acting in cancer genomes
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Gene Regulation You are fluent in English Desirable but not required/ Nice to have Computational Biology Skills Experience with RNA analysis Education and training You hold a BSc or master's in molecular