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Max Planck Institute of Molecular Physiology, Dortmund | Dortmund, Nordrhein Westfalen | Germany | about 1 month ago
and investigating the potential of novel algorithmic and statistical solutions to foster the creation of new computational tools. The position provides opportunities for collaboration with both internal
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series of turbidity, light attenuation, Secchi depth and photosynthetically active radiation (PAR) based on in situ, remotely sensed and modelled data. Conducting a statistical ensemble analysis of
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preprocessing methods for instrumental platforms Work on integration of LC-MS/MS derived metabolite annotation into MS imaging workflows Multivariate statistics (including machine learning, neural networks etc
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quantitative training or research experience Training and experience in quasi-experimental methods is a plus Strong coding skills in R, Stata, or other statistical software package Good communication skills in
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criteria: Proven track record of publishing high-quality scientific articles in peer-reviewed journals. Excellent command of written and spoken English. Proficiency with advanced statistical methods
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | about 2 months ago
, elasticity theory, statistical physics, or biological physics is a plus. Programming skills are highly desirable. Fluency in both written and spoken English is required. The researcher should show eagerness
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candidates with experience in software design, Python and CUDA coding, molecular dynamics calculations, and model building. Knowledge in physical chemistry, Bayesian statistics, machine learning, computational
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or inflammatory processes, e.g., during organ development or tissue regeneration. Your tasks: Bioinformatic, statistical, and machine learning-based analysis of experimental, data generated via a broad spectrum of
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geographic information systems (GIS) and programming languages (e.g. Python, Matlab, R) as well as in advanced statistical methods for analyzing complex ecosystem and environmental datasets. Good knowledge
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or bioinformatics with strong experience in applied omics research Knowledge in programming languages and statistical analysis Experience with the analysis and integration of high throughput data such as NGS and