OGPS Research in Motion: Project Management for Biomedical Scientists

Biomedical research projects rarely unfold exactly as planned. Experiments fail, timelines shift, new priorities emerge, and progress often depends on collaborators, shared resources, and decisions outside your control. Project-management strategies can help researchers navigate that complexity without trying to eliminate the uncertainty that is inherent to science.

In this interactive workshop, participants will explore foundational project-management concepts and learn how selected Agile practices can be adapted for biomedical research. Using research-relevant examples, we will consider practical approaches to breaking complex projects into manageable work, setting priorities, making progress visible, identifying obstacles, and adjusting plans as new information emerges.

Participants will leave with strategies they can apply immediately to their own research projects while developing project-management skills that transfer across scientific and professional settings.

By the end of this session, participants will be able to:

• Apply foundational project-management concepts to biomedical research projects.
• Break complex research goals into smaller, actionable pieces of work.
• Use prioritization and workflow-management strategies to focus effort and make progress visible.
• Identify project dependencies, constraints, and potential bottlenecks.
• Adapt plans when research findings, timelines, or priorities change.
• Recognize project-management skills they are developing through their research and how those skills translate to future careers.

Archer Careers Resource

This workshop will complement the Archer Careers Build Skills | Project Management for Life Scientists course available to U-M trainees. Participants are encouraged to explore the course before or after the workshop to deepen their understanding of project-management principles and their application in the life sciences.

Generative AI can help researchers plan, organize, communicate, and document their work—but using AI effectively requires more than knowing how to write a prompt. Researchers also need to determine where AI adds value, where human judgment remains essential, and what information is appropriate to share with different AI systems.

In this practical workshop, Dr. Shayla Vradenburgh will explore how AI tools and project-management principles intersect in biomedical research. Participants will examine ways AI can support common project-management tasks such as breaking down complex projects, developing timelines and action plans, preparing meeting agendas and follow-up documentation, communicating project status, identifying potential risks or gaps, and maintaining momentum across multiple priorities.

The session will also address responsible AI use in research environments, including the importance of verifying AI-generated output, protecting sensitive information, documenting appropriate uses, and recognizing tasks for which AI is not an appropriate substitute for researcher expertise or professional judgment.

Participants will leave with practical approaches they can adapt to their own research workflows and a framework for deciding when—and when not—to use AI as a project-management tool.

By the end of this session, participants will be able to:

• Identify research project-management tasks for which generative AI may be useful.
• Use AI to support planning, prioritization, communication, and documentation.
• Develop prompts that provide sufficient context, constraints, and desired outputs for project-management tasks.
• Evaluate AI-generated outputs rather than treating them as authoritative.
• Recognize privacy, security, research-integrity, and other considerations when using AI in research workflows.
• Identify opportunities to integrate AI selectively and responsibly into their existing project-management practices.