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, PowerPoint and statistical software are expected. Over the course of your role, you will be interacting with computational design pipelines and will be expected to acquire basic proficiency in Python. Your
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(e.g. R, Python) and an ability to work with large datasets Strong record of peer-reviewed publications Ability to independently design and execute experiments and interpret data Ability to work in a
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-wide association studies. Excellent programming skills in e.g. C, Perl, R, Python Knowledge and prior experience of work with high performance computation environments Previous experience in projects
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record in peer-reviewed international journals Experience with remote sensing, LiDAR, and GIS applications Programming skills in Python Background in LiDAR point-cloud analysis and vegetation structure
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learning models (e.g., PCA, PLS-DA, clustering, CNNs) to classify microplastic particles based on spectral and morphological fluorescence data. Develop and maintain modular analysis pipelines in Python
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tools like ViennaRNA and NUPACK) and MD simulations (e.g., with GROMACS). Strong skills in statistical data analysis and machine learning in Python and R are expected, along with experience working in
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algorithms. Good coding skills in Python, PyTorch, together with a general interest in biology are welcomed. Application Applications should contain a CV, a motivation letter, and the names and contact
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., dissection, viral delivery, histology) Mouse surgery experience, especially surgeries involving embryonic mice Computational experience (R, Python, or equivalent) or a strong interest in developing
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Familiarity with omics approaches such as scRNA-seq, proteomics Programming or data analysis skills such as R, Python, or similar Experience in international collaborative projects Experience with laboratory
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required). Experience with quantitative analysis of imaging data (e.g. Python, MATLAB, or equivalent). Track record of first-author publications demonstrating methodological or conceptual contributions