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will exhibit very low signal-to-noise ratio and extremely weak contrast, which makes this research very challenging. You will use statistics-based methods to measure unknown structure parameters
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What do we expect from you? You hold a M.Sc. degree in Physical Geography, Earth Sciences, Ecology, Remote Sensing, Geoinformatics, Engineering, or related fields. You have strong statistical, analytical
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to analyse complicated data. Good statistical knowledge and experience with geo-spatial analysis techniques is a benefit. Candidates should be capable of planning and organizing their own work independently
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quantifying population-level intervention effects, there is a risk of oversimplifying causal queries and of neglecting the rich history and efficacy of statistical modeling techniques. This ERC project aims
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of gene regulatory mechanisms statistical analysis basic processing of NGS data experience with iPSC culturing knowledge of and some experience with genetic perturbation assays, such as CRISPR What we offer
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Python Ability to adapt to the research environments while being full members of two labs Desirable skills knowledge of gene regulatory mechanisms statistical analysis basic processing of NGS data
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: structuring and processing the results obtained. Statistical knowledge is required (data mining, hierarchical cluster analyses, survival analysis, machine learning). Job profile You hold a master's degree
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, Revio) is advantageous. Bioinformatics Skills: Proficiency in Python and R for data analysis, visualization, and statistical modeling. Experience with bioinformatics tools commonly used in genome research
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signalling towards personalized medicine, using statistics, bioinformatics and machine learning, as well as high-throughput biology in the framework of gene regulatory networks. Our final goal is to use
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motivated to obtain your PhD. You possess good methodological and statistical skills, and are willing to develop those further. You have experience with SPSS or R. You have good scientific writing and