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Vanishing Gradients

Episode 18: Research Data Science in Biotech

May 24, 2023
Eric Ma, a leader in the research team at Moderna Therapeutics, discusses the tools and techniques used for drug discovery, the importance of machine learning and Bayesian inference, and the cultural questions surrounding hiring and management in research data science in biotech. They also explore the tech stack used in their work, the skills and hiring considerations in biotech, the importance of data testing and standardizing Excel spreadsheets, and the current state and challenges of Bayesian inference.
01:12:42

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Quick takeaways

  • The importance of employing tools and techniques like MINA, machine learning, deep learning, Bayesian inference, and open-source software like Python in the biotech industry for drug discovery.
  • The challenges and rewards of transitioning from an individual contributor to a team lead in the biotech research industry, emphasizing the need for coaching and guiding teammates to produce high-quality work.

Deep dives

Research data science in biotech: Tools and techniques for drug discovery

In this podcast episode, Eric Ma discusses research data science in the biotech industry. He highlights the importance of employing tools and techniques such as MINA, machine learning, deep learning, Bayesian inference, and open-source software like Python. The focus is on solving problems related to drug discovery, including target identification, molecule discovery, and vaccine design. Eric emphasizes the need for models to be differentiable, allowing for joint optimization and efficient experimentation. He also discusses the transition from being an individual contributor to a team lead, emphasizing the importance of coaching and guiding teammates to produce high-quality work.

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