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energy-intensive infrastructures. Implementing algorithms and simulation models using Python, MATLAB, Julia, or other suitable tools. Analysing simulation and project data, and validating the developed
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experience with high-performance computing (HPC) systems; Ability to interact with data and software programmatically (for example, familiarity with Python scripting) Strong command of written and
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surveys with human participants using platforms like Empirica or similar. Running social simulations with AI agents using platforms like Concordia or similar. Coding in Python or a similar language for
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Experience in computational analysis of biological data Experience with single-cell, transcriptomics, spatial biology, or other omics data analysis approaches Programming skills in R, Python, or
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R, Python, or equivalent Ability to work independently while flexibly contributing actively to an interdisciplinary research team Sufficient communication skills and fluency in English We especially
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experience is considered an advantage: Antimicrobial resistance research Metagenomics, microbial genomics, or bioinformatics Statistical programming in R or Python High-performance computing environments
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conduct research on the topic. Have programming skills (e.g., Python) and experience with numerical simulations or quantum software frameworks (e.g., Qiskit and PennyLane). Have a demonstrated ability to
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advantage. Good data-analysis and programming skills (e.g., Python, MATLAB, or similar). A hands-on approach to experiments, patience in troubleshooting, good communication skills, and the ability to
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before the application deadline. Have a solid background in quantum computing and quantum algorithms, sufficient to conduct research on the topic. Have programming skills (e.g., Python) and
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learning and generative models. Programming skills suitable for modern machine learning research, preferably including Python and deep learning frameworks. Interest in one or more of the following areas