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; Proven competence on flow measurement techniques and PIV; Familiarity with optics, lasers, image processing and statistical data analysis Familiarity with flow modelling techniques (CFD) or machine
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sequencing data generation and interpretation Bioinformatics and statistical analysis, to characterize genome evolution, mutation processes, and adaptation patterns The PhD candidate will progressively
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sequencing data generation and interpretation Bioinformatics and statistical analysis, to characterize genome evolution, mutation processes, and adaptation patterns The PhD candidate will progressively
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skills (e.g., numerical methods, statistical analysis, coding, data management) Good communication skills Ability to work in a team Driving license category B desirable (access to field sites) Your Tasks
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large-scale omics datasets, develop and apply statistical methods and interpretable AI models, and contribute to the identification of biological markers and molecular mechanisms associated with disease
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publish scientific articles related to the research project. You will collaborate with other project members (PhDs, postdocs, principal and co-investigators). You will participate actively in seminars
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high-frequency or “flash” trading based on sheer speed of execution might have reached its limit, we see continued opportunities with our strategy of using statistical research to outsmart
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software developed concurrently by a postdoc in our team. The successful applicant will be an integral member of the GreenTE community, which offers an open, diverse and inspiring environment to engage in
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program more than 260 PhD students and 200 postdocs will be part of the Research School. The DDLS program has four strategic research areas: cell and molecular biology, evolution and biodiversity, precision
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Development Design new statistical and machine learning models tailored to this emerging omics modality. Multimodal Data Analysis Work with high-dimensional datasets combining quantitative RNA features