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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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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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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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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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to answer questions about mutational processes and selective pressures in cancer tumors. The candidate will analyze data, develop models for the description of tumor DNA sequencing data, develop a
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modeling to answer questions about mutational processes and selective pressures in cancer tumors. The candidate will analyze data, develop models for the description of tumor DNA sequencing data, develop a
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curiosity-driven Desirable but not required/ Nice to have Experience in super-resolution imaging, optics, and a basic knowledge of computational biology Education and training You hold a Phd in biology
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bioinformatic tools Desirable but not required/ Nice to have Familiarity with deep learning methods/ protein language models Education and training A master's degree (or equivalent) (or equivalent) in
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laboratory techniques, including molecular biology, protein expression, purification, and characterization Desirable but not required/ Nice to have Experience in enzymatic and ligand-binding assays Education