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Demonstrated proficiency with Python, and machine learning libraries; pytorch, sklearn Experience with transformer architectures, and interpretable AI methods and libraries, concept-bottleneck architectures
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. PyTorch, Jax, scikit-learn) applied to genomic datasets Experience with various sequence modeling architectures and interpretable AI methods (attribution methods including SHAP, Integrated Gradients, etc
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leveraging collaborations within the group and across Research & Development. Who You Are: PhD in Computational Biology, Computer Science, Applied Mathematics, or similar field Demonstrated record
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architectures, and interpretable AI methods and libraries, concept-bottleneck architectures, attribution packages: shap, captum, etc. Experience with bulk and/or single-cell omics data analysis (e.g. bulk
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hypotheses. This is a fantastic opportunity to contribute to world-class science in a leading biotechnology company. Who you are: Candidates must have a PhD in Computational Biology or Computational Science
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streamline and accelerate the development of the projects. Share research through scientific publications, national and international conferences, and internal presentations. Who You Are: PhD graduate in