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, preferably in Python or R, and experience in the Linux environment Experience with large-scale data analysis, such as genomics or transcriptomics data Experience with a workflow management system such as
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aspects of Cultural Heritage Science and the challenges inherent to this field (experimental noise, few-data regime) will have to deploy deep learning algorithms using Python/Keras/Pytorch or equivalent
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strong motivation to work in a multidisciplinary team; Experience with quantum mechanical software packages (VASP, CP2K, …), machine learning potentials (SchNet, NequIP, MACE), and coding (Python, C
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skills in at least one relevant language (e.g., Python, R, Rust, JavaScript) Familiarity with smart contract interaction (e.g., web3.py/ethers.js, Solidity/Vyper, sub-graph indexing), and local development
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the Global South is a strong advantage. - Good knowledge of statistical methods and relevant software packages (e.g. R, Python). We also encourage candidates who do not meet every single requirement but
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, classification, and topic modeling). You are comfortable with programming and analysis in R, including tidyverse, reticulate, tidymodels, etc. You are comfortable programming in Python and working with relevant
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programming (Python) and Linux skills is a must Knowledge in plant biology or single-cell genomics is a plus You have good communication skills, are a team player, and are proficient in English We offer a 3
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, Machine Learning, Physics, Mathematics, Engineering, or equivalent A solid publication record with research publication(s) in peer-reviewed international journals Good programming skills (ideally in Python
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Programming skills in Python Experience with Machine learning (PyTorch/Keras). A computational mindset and a strong interest in computational biology We offer A versatile and challenging job with
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publications. You have experience in the computational analysis of single cell and/or transcriptomics data using R/Python. Wet lab experience is beneficial but not essential. You have a strong enthusiasm for