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transform our understanding of pathogens, their interactions with hosts and the environment, and how they are transmitted through populations. Research will have a strong focus on computational analysis
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will be entirely computational, focusing on the large-scale bioinformatic analysis of proteome data from a wide range of existing species. The research will focus on understanding mutational robustness
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. Candidates are further expected to have experience in processing and analyzing high-throughput genomic sequencing data and in statistical analysis. Previous experience with Drosophila melanogaster or other
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, and will apply deep learning to integrate the analysis flows. The PhD student will develop the method and apply to numerous in-house samples of environmental sequences, pushing the boundaries of RNA
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: Knowledge of theory of population genetics Experience with analysis of whole-genome DNA sequence data (Nanopore, PacBio, and/or Illumina) Experience with the generation and analysis of sequence data from
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research field Excellent written and spoken English Merits In addition, experience in the following areas will be considered: Knowledge of theory of population genetics Experience with analysis of whole
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scientific knowledge. The ideal candidate will possess a strong background in data analysis, excellent problem-solving skills, and the ability to thrive in a collaborative and interdisciplinary environment. As
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interactions. The project will involve: Optimizing crystallization conditions for protein micro- and nanocrystals. Testing and improving data collection and processing workflows for protein structural analysis