
Learn, reflect and lead
The ͵ÅÄ͵¿ú and ͵ÅÄ͵¿ú Biology Education and Professional Development Committee will present three symposia on distinct but essential matters in BMB education at , the society’s annual meeting, in Seattle in March.
One symposium will be about artificial intelligence. A lot of people think of AI as in the future, but in fact it is already here. It is changing the way biomedical research is conducted. How do we introduce students to BMB while intertwining AI and machine learning so that they will learn to think like biochemists and data scientists? The goal of this session will be to see how others have brought AI tools into the classroom to make this material accessible to all students.
Another will be about intentional leadership development. How do we help people learn and grow to work toward a common goal? This session will focus on navigating the tough parts of leadership. We’ll cover leading in fast-changing environments, working with difficult people and sustaining effective leadership.
The third will be about cultural humility — the dynamic, lifelong process of self-reflection and self-evaluation yielding insights about our identities and biases. This process affects how we show up in our classrooms to provide an inclusive environment where we can create future STEM leaders.
Keywords: Artificial intelligence, cultural humility, professional development, big data, machine learning, biases, leadership, education, inclusive excellence.
Who should attend: Faculty, educators, graduate students, postdocs and administrators.
Theme song: “Golden” by Jill Scott or “Man in the Mirror” by Michael Jackson.
This session is powered by what it takes to build STEM leaders for the future.
The complete list
Learn about all 11 symposia planned for Discover BMB 2023:- Protein Machines and Disorder
- Regulation of RNA
- Organelles, Mechanisms and Phase Properties of Cellular Quality Control
- Lipid Dynamics and Signals in Membrane and Protein Structure
- Frontiers in Carbohydrate Synthesis and Recognition
- Bias In, Bias Out in Data Science
- Cell Signaling — New Tools and Emerging Concepts
- Education and Professional Development
- Biochemistry of Elemental Cycling
- Advances in Organismal and Cellular Metabolism
- Artificial Intelligence and Machine Learning in Structural Biology, Drug Design and Systems Biology
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