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biomedical research. Programming skills in Python and/or R, and experience developing, implementing, and evaluating computational or machine learning methods. Solid knowledge of statistics, biostatistics, and
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coding as well as skills in another programming language such as Python or R for analysis and visualization of single-cell RNA sequencing is a requirement. Knowledge of statistics, AI/ML, mathematical
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(e.g., R and Python). Meritorious will be considered experience in Microscopy-based imaging, Immunohistochemistry, and cell culture differentiation protocols. You are a curiosity-drive person, fascinated
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programming in Python and Bash and working in HPC environments using workflow managers such as Snakemake or Nextflow. Experience in the analysis of pancreatic islet or pancreas single-cell genomic datasets is
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. In addition, the following are requirements for the role: Strong programming and quantitative skills, particularly in Python and/or R. Experience in deep learning, machine learning, or large-scale
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higher education credits (ECTS). Relevant courses include, for example, image processing, computer vision, machine learning, deep learning and neural networks, as well as courses in Python, GPU programming
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language (C++, Python, Rust, …) One high-quality first-author paper (journal or top-tier conference) You are expected to be somewhat accustomed to teaching, and to demonstrate good potential within research
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. Documented research experience in modern deep learning (e.g. generative models, Bayesian deep learning or large pre-trained models) and excellent programming skills in Python and a modern deep learning
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models and/or probabilistic modelling, and excellent programming skills in Python and a modern deep learning framework (e.g., PyTorch or JAX) are required. Excellent skills in spoken and written English
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are a strong merit but not a requirement. Programming knowledge in Python, and experience of data science tools such as Numpy, Pandas or Matplotlib is a merit, as well as experience of using modern deep