Machine Learning Software Engineer
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El puesto
Design, build, and deploy production-grade ML models to optimize lipid nanoparticle (LNP) formulation, synthesis, and in vivo performance.
Develop scalable software practices for uncertainty quantification to enable reliable real-time decision-making.
Engineer robust data pipelines to integrate multi-fidelity datasets (in silico and in vivo) to accelerate data-driven discovery of novel LNPs.
Collaborate with computational scientists to translate research models into maintainable software that identifies design pathways for LNPs achieving targeted properties.
Work with infrastructure and automation teams to architect and streamline real-time data transfer between predictive models and experimental platforms.
Partner with experimental teams to drive iterative DMTA cycles and communicate findings to stakeholders.
Develop scalable software practices for uncertainty quantification to enable reliable real-time decision-making.
Engineer robust data pipelines to integrate multi-fidelity datasets (in silico and in vivo) to accelerate data-driven discovery of novel LNPs.
Collaborate with computational scientists to translate research models into maintainable software that identifies design pathways for LNPs achieving targeted properties.
Work with infrastructure and automation teams to architect and streamline real-time data transfer between predictive models and experimental platforms.
Partner with experimental teams to drive iterative DMTA cycles and communicate findings to stakeholders.
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