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Field
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comparing model predictions of observed transient data Experience in software development with larger scientific codes; in particular, expertise in Fortran, C, Python, and/or build systems are of advantage As
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modelling reduced‑order or low‑order modelling scientific programming (e.g. Python, MATLAB, etc.) You should be able to work independently and collaboratively, communicate your research clearly, and
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environments such as R, Java, Python, C++; Ability to communicate statistical concepts and data analysis interpretations to the group; Experience in genetic analysis of environmental exposure risk factors
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microscopy, antibody-based techniques, small molecules/ligand-trap based therapies Preferred qualifications Experience with bioinformatic analysis using R and/or Python. Experience with molecular/cellular
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with omics data analysis, biostatistics, and image analysis tools. Strong programming skills (R, Python) and knowledge of relevant databases and pipelines. Candidates with peer-reviewed publications
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, math, statistics, and/or computer science Experience with programming, data science, and geospatial analysis (especially R, Stata, Julia, MATLAB, or Python) An enthusiasm for empirical research and an
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or tools and methodologies for dynamical simulation. programming skills in Python, MATLAB, Modelica and/or domain specific tools used for energy system modelling and simulations. Emphasis is also placed
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and sensor data analysis Experience in remote sensing with satellites Experience in analytics in biogeochemistry, microbial ecology, and field work in aquatic environment Experience in Python, GIS
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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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biogeochemistry, microbial ecology, and field work in aquatic environment Experience in Python, GIS, or equivalent tools for environmental data-analysis Familiarity with computational flow dynamics modelling