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interventions. Candidates need to be able to understand statistical modelling, have a mathematical background, and be fluent in R programming. We will also consider candidates who have extensive C++ or Python
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Max Planck Institute for Heart and Lung Research, Bad Nauheim | Bad Nauheim, Hessen | Germany | 3 months ago
spatial transcriptomics; become a technical expert the group relies upon Conduct rigorous multi-omics data analysis using R or Python; generate publication-quality findings Your qualifications A strong
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(e.g., Python, Julia, Fortran, C++, MATLAB) and experience with high-performance computing environments Demonstrated publication record in reputable peer-reviewed journals Excellent written and oral
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software and research at www.cernaklab.com Required Qualifications* Candidate must have strong programming skills in Python, React, JavaScript and related languages. Expertise in one or more of the following
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of the relevant fields. Preferred skills: Previous experience in computational ecology and statistics. R or Python. Statistical analysis tools such as NIMBLE, JAGS or STAN. Familiarity with data processing, quality
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biochemistry or analytical chemistry. An expert understanding of mass spectrometry, and its application for peptide and protein analytics in a dynamic research environment. A good understanding of Python
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. · Expertise in working with large datasets and developing quantitative models. · Documented experience in programming languages such as Python, R, or VBA. · Proficiency in Excel and PowerPoint. · Experience
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motivated Postdoctoral Fellow with strong expertise in RNA-seq and multi-omics data analysis. Candidates should be proficient in Python and/or R and have a solid background in Biology, Computational Biology
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externally (e.g., conferences) Required: PhD in Bioinformatics, Computer Science, Computational Biology, or related field Experience analyzing DNA sequencing data Proficiency in Python and/or R Familiarity
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statistical software (e.g., R, Stata, SPSS, Python) • Expertise in quantitative analysis, with preferred skills in o Quasi-experimental evaluation techniques (e.g., Difference-in-difference, PSM) o Social