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bioinformatics, statistics, and/or computer science to join the Eberlin Lab for Medical Mass Spectrometry. These skills would be applied to large mass spectrometry and mass spectrometry imaging datasets
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Posting Number 25FA0789 Posting Open Date 08/18/2025 Posting Close Date 08/29/2025 Qualifications Minimum Education and Experience Doctoral degree in Computer Science, Marketing, Economics, Statistics
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, statistics, and/or computer science. These skills would be applied to large mass spectrometry and mass spectrometry imaging datasets for clinical research, focusing on malignancies including breast and lung
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interdisciplinary project on the development of new computational approaches for improving safety and sustainability of (nano)materials based on publicly available data and tools, including omics data, and
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the field of public health, biostatistics, pharmacoepidemiology and epidemiological studies. They must be proficient in data analysis using statistical or computer modelling software, such as Stata or R
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of cancer. This is a 3-year flexible program with personalized educational curricula and individually tailored multidisciplinary teams of mentors with ongoing research in a variety of pediatric and adult
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software and high-performance computing (HPC). These include particle and gravitational physics. -On the data analysis side, the group designs novel statistical methods for particle physics and astrophysics
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | about 4 hours ago
postdoctoral researchers, students, and visitors. The research The postdoctoral researchers will engage in theoretical and computational research in Nonequilibrium Statistical Physics and Active Matter. For more
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, United States of America [map ] Subject Areas: Mathematics / applied mathmetics , Mathematical Sciences , Partial Differential Equations , Statistics Machine Learning Computer Science Appl Deadline: none (posted 2025/08
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to at least the intermediate level of multiple regression Computer literacy with knowledge of at least one statistical software package (e.g., R, Mplus, Stata, SAS) Working collaboratively and effectively with