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Your focus area will be Personalized Health Care and Companion Diagnostics.
You will act as a project statistician/data scientist to support development of new biomarkers and companion diagnostics.
You will be responsible for planning and analysis of pre-clinical and clinical studies.
You will interact daily with project stakeholders (R&D, clinical science, regulatory, business, external partners and customers) to capture requirements for data analysis and communicate back the results.
You will have a chance to apply state-of-the-art multivariate machine learning techniques for development of novel clinical algorithms.
University degree in (bio)statistics or related subjects (e.g. bioinformatics, mathematics, physics) with substantial experience in statistics; preferably with a Ph.D.
Experience in life science/diagnostics/pharmaceutical industry or successful completion of clinical data analysis projects in academia
Expertise in statistical methods, such as classification, survival and longitudinal models
You are familiar with diagnostic statistical procedures: method comparison, logistics regression, ROC analysis, cut-off determination, bridging studies
Experience in design, analysis and evaluation of pre-clinical and clinical studies
Excellent knowledge of R and ideally Latex, knitr or R markdown
Enthusiasm to learn and implement new statistical methodology