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Field
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circuits and electronics integration. It is desirable that the candidates have sound knowledge in statistical analysis of device output and have experience with failure analysis. The role holder will work
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Laboratory techniques for sample preparation Analysis of mass spectrometric datasets and statistical calculations Contribute to in vitro analyses Contribute to carrying out animal experiments Contribute
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analytical methods for the analysis of linked data from electronic health records and genomic or molecular sources. Strong statistical skills (e.g. proficiency in R or Stata), along with excellent writing
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scan data is desired Familiarity with analytical tools such as R or Python for statistical and phylogenetic comparative analyses Experience with scientific writing and publishing in peer-reviewed
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strongrecord of scientific productivity is preferable. The successful applicant must have a Ph.D.in Computer Science, Data Science, Statistics, Mathematics, Physics, Engineering orrelated field at the start of
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in a relevant discipline, such as medical statistics, and practical experience applying research skills to deliver high-quality outputs within specified timelines. A PhD, or ongoing PhD studies, in a
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, statistical analysis, and comparison of experimental results with theoretical predictions. Analytical and Problem-Solving Skills: Strong analytical thinking with the ability to troubleshoot complex experimental
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. Experience with laboratory and field testing of sensors or similar devices, including performance evaluation. Proficiency in data management, statistical analysis, and comparison of experimental results with
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models and data-driven longitudinal statistical analysis. The successful applicant will have access to a variety of datasets covering diabetes, AMD, Glaucoma and rare genetic retinal diseases. With
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the position Demonstrated expertise in organization and analysis of quantitative datasets and statistical modeling in Stata or R Excellent written, verbal, and interpersonal communication skills