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in one or more languages such as R, Python, C/C++, or Perl. Experience with high-performance computing environments is an advantage. Excellent understanding of statistics and experience with complex
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Programming skills in one or more relevant languages (e.g. Python, R, Bash) Experience with the analysis of omics data (e.g. genomics, metagenomics, metatranscriptomics); experience with additional data types
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parallel and distributed systems, including performance tuning Programming and tooling such as C/C++, Python, CUDA, OpenMP, and Spack Linux-based systems, scripting, Slurm, and general systems engineering
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modelling and analysis is a strong asset. You are proficient working with programming languages such as Python, MATLAB, or similar, and are interested in combining analytical modelling with data-driven or AI
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working with multimodal data fusion and high-resolution remotely sensed data is required. Proficiency in programming, particularly in Python, is essential. Knowledge of deep learning approaches and
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. Implement high-performance C++ and Python modules for simulation, rendering, and data processing. Explore and integrate deep learning techniques into graphics and simulation pipelines (e.g., PyTorch, JAX
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) Familiarity with automation software (e. g. Hamilton Venus), scripting, or workflow scheduling (e.g. HighRes Cellario) and experience with standard programming languages such as Python, C++, Matlab or R
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, Python, RStudio IDE, VS Code) You know your way around the collection of R Tidyverse packages, and you are a competent practitioner in solving problems as outlined in the book R for Data Science You stay
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project administration Profile You hold an architectural or advanced technical degree corresponding to FHEQ Level 7 You have a strong interest in programming and, ideally, experience with Python and C
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analysis procedures and computer tools for automated data acquisition/processing (Python/C++/Labview programming languages), Team player with excellent communication skills and collaborative working style