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Field
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optimization and logistics management. Data analysis and project management skills. Strong understanding of optimization concepts and profitability. In-depth knowledge of environmental sustainability standards
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) Knowledge of intersectionality-informed approaches to research including in data collection and analysis. Good collaboration skills, including with people with lived experiences, other research and academic
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data analysis for omics studies, including genotype data, bulk and single-cell RNA sequencing data, high-dimensional phenotype data, pathway and functional analysis, network analysis, polygenic risk
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skills in data analysis, machine learning, as well as in mathematical and computational modelling? You will have the opportunity to investigate innovative solutions using machine learning algorithms and
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Max Planck Institute for Astronomy, Heidelberg | Heidelberg, Baden W rttemberg | Germany | about 2 months ago
, JWST, VLT/MUSE and more instruments. Depending on the exact position, candidates with prior experience in handling ALMA, HST and/or JWST imaging data, molecular gas (structure) analysis, (stellar
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analysis Papers published from the PhD Desirable criteria Knowledge of the cerebral cortex Ability to design and troubleshoot research questions Downloading a copy of our Job Description Full details
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, metabolomics/data analysis is highly desirable. Preferred Qualifications Equipment Utilized Physical Demands and Work Environment Overview This postdoctoral associate position is available immediately to work
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data analysis. Record of scholarly publications and scientific communication skills Proficiency in statistical and data analysis tools (e.g., MATLAB, Python, R). Preferred Qualifications: Experience with
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are expected to utilize computational, biochemical, functional, and in vivo approaches including RNA omics and bioinformatics approaches. Experience with tools of RNA sequence analysis is desired. Minimum
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analysis with practically motivated case studies, offering a strong foundation for researchers interested in advancing the mathematical understanding of geometric deep learning. Your Qualifications PhD