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for variant effect prediction. Good knowledge of human prehistory and human evolution. Good knowledge of statistics. Training in bioinformatics, genomics, molecular genetics is advantageous. How to apply
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diversity and mutational robustness, the student will conduct a variety of statistical analyses. Further projects could include assessing whether adaptive substitution rates relate to degree of mutational
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, probability theory, etc) A competence in quantitative topics equivalent to a mathematics, statistics, physics, computer science, or engineering degree is required (if your degree was not in one of these domains
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an asset. Additional qualifications Working knowledge in statistics and infection biology is highly appreciated. Part of the DDLS program, to be employed as a PhD student, the applicant must be
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networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid academic background with thorough computational and
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techniques coupled to high resolving mass spectrometry for molecular characterization, using tandem mass spectrometry and reactive chemistry, quantification, and data analysis, including statistics. Variations
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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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Lepidoptera and plant ecology Statistics and programming (e.g. in R) The application should consist of the following (all files in PDF-format): Curriculum vitae including publication list, Master [alternatively
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meritorious. Knowledge in statistics, AI/ML, single-cell genomics and/or phylogenetics is further meriting. Personal characteristics, such as a high level of creativity, curiosity, thoroughness, and/or a