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in dynamical systems modeling (ODEs) and machine learning and very strong programming skills (Java, Python). A background in evolutionary genomics research is a strong plus, as is previous experience
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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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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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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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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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: Proficient in Python. Machine Learning: Strong experience with frameworks like TensorFlow, Keras, or PyTorch. Preferred Skills: Experience with Explainable AI (e.g., SHAP, Integrated Gradients
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Programming experience in Python Excellent communication skills and fluency in English Collaborative personality with attention for detail Bonus but not required Experience in imaging or spatial omics data
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(preferred) or Snakemake Practical knowledge of R/Bioconductor and one scripting/programming language (Python or equivalent) is essential. Practical knowledge in using Linux servers is essential - Working
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programming or scripting skills (e.g., Python, MATLAB, Bash) are a plus Prior experience in amyloid biology, protein aggregation, or disease-related structural research are an advantage. Ability
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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