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and generative protein design (e.g. AlphaFold, OpenFold, Boltz, Chai). Develop robust, reproducible and reusable Python code for model training, inference, and large‑scale computational experiments. Run
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). Develop robust, reproducible and reusable Python code for model training, inference, and large‑scale computational experiments. Run and manage high‑throughput workloads on HPC or cloud infrastructure
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past successes: https://europepmc.org/article/MED/35021063 , https://europepmc.org/article/MED/31819264 , https://europepmc.org/article/MED/31561945 , https://europepmc.org/article/MED/39747019 , https
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. Practical experience applying machine learning or deep learning methods to biological data. Proficient in Python, with working knowledge of bash and experience using HPC or cluster environments (e.g. SLURM
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development, optimization, and continuous learning in a rapidly evolving field. Desirable: experience with multi‑omics datasets, single‑cell or spatial technologies, or basic scripting skills (R/Python). Our
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open-source software packages and set up computational pipelines. As a bio-informatics research lab, we publish software packages in Python and R for specific, cutting-edge analysis of large-scale
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. Proficient in Python, with working knowledge of bash and experience using HPC or cluster environments (e.g. SLURM). A pragmatic scientist who combines technical depth with a clear translational, goal‑oriented
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collaboration with AI experts. Your Profile PhD or equivalent experience in Bioinformatics, Computational Biology, Computer Science, or related fields. Strong programming skills in Python and/or R. Experience
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ample opportunities for direct validation in biologically relevant settings. This interdisciplinary atmosphere has been a main catalyst for many past successes: https://europepmc.org/article/MED/35021063
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experience. Proficiency in Python. Experience with data analysis, machine learning, and AI methods. Motivation to tackle a challenging multi-disciplinary project. Bonus (but not required) Experience with