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, and contribute to identifying tumor vulnerabilities that may become future therapeutic targets. What we offer: A dynamic and interdisciplinary research team with expertise in cancer biology, statistics
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: Mathematics, Mathematical Statistics and Computational Mathematics. The research at the Division of Computational Mathematics covers many different areas in numerical analysis, symbolic computations
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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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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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, engineering physics, biomedicine, or similar Documented skills in data-driven analysis (machine learning using python with TensorFlow, PyTorch, or similar) and computational statistics Specific knowledge of big
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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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vision, machine learning, deep learning and neural networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid
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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