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analysis and analytical data analysis workflows, together with other team members Implementing AI-based microscopy image analysis software as python packages Developing algorithms to deploy machine learning
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. Strong knowledge of quantitative and/or computational research methods, ideally in econometric analysis or optimization and simulation models. Preferable knowledge in Python and STATA. A collaborative team
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and statistical data analysis Excellent written and spoken English skills Experience with TMS and proficiency in relevant software (e.g., MATLAB, R, Python, or SPSS) is an advantage Key responsibilities
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academic area such as applied mathematics, computer science, physics, biomedical or electrical engineering or similar disciplines. Good programming expertise (Matlab, C++, Python or equivalent) and
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hands-on experience in molecular cloning, cell culture systems, mouse models, and interest in liver disease biology. Experience with R or Python and the computational analysis of next-generation
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of Unix systems (GNU Linux) and keen to gain hands-on experience in Networks and systems Machine Learning knowledge is a plus Strong analytical and programming skills are required (Python, Matlab, Golang
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-level data on single cell level, R/Bioconductor and Python/Tensorflow will be useful but is not a requirement. An experimental researcher with an interest in methodologically driven cancer research
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interest in historical research, migration, and digital infrastructures Familiarity with digital tools and languages such as Wikibase, SPARQL, RDF, Python, GitHub, and Jupyter Notebooks is highly desirable
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publication record #excellent programming skills in Python or at least one other scientific programming language (e.g. FORTRAN, C, Matlab, R) #good knowledge of English (written and oral) #high degree
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, qPCR, digital PCR, amongst others. Sequencing data analysis will be done using data analysis pipelines (Python, R) on the high-performance computing (HPC) infrastructure. About the TOBI lab