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We’re seeking a Project Director to operationalize scientific programs that develop and scale Arcadia’s experimental and computational biology platforms, including areas such as high dimensional phenotyping, molecular genetics, and protein design. This role is ideal for a PhD scientist who thrives at the interface of science and management—an operator who amplifies scientific leadership by bringing structure, focus, and coordination to their efforts. Strong candidates can quickly translate high-level scientific goals into actionable research plans, guide experimental progress, and ensure effective collaboration and communication across teams.
Job Responsibility:
Operationalize scientific programs that develop and scale Arcadia’s experimental and computational biology platforms
Manage a small group of scientists who are responsible for executing the scientific agenda set by a scientific leadership
Turn research goals into concrete roadmaps, manage cross-functional dependencies, and ensure efficient execution across projects
Help prioritize work, set milestones, identify bottlenecks, and ensure your team is resourced, aligned, and focused
Drive communication about research progress across teams, scientific program leads, and leadership to ensure alignment and allow effective, rapid iteration
Requirements:
PhD in the life sciences or a related field, and at least three years of post-PhD work
3+ years leading complex, multi-stakeholder research and development projects or programs in a fast-paced, goal-oriented environment
Familiarity with research operations or project management tools
Experience developing complex experimental and/or computational workflows (for example, high-throughput assays, molecular or optical methods, or modeling/design pipelines)
Demonstrated ability to design and deliver structured execution in dynamic, research-driven environments
Exceptional communication, organization, and facilitation skills
Experience supervising or mentoring scientists
Comfort navigating ambiguity and helping others make progress through it
Nice to have:
Experience in high throughput molecular assays, genetic perturbation screens, or imaging-based multi-dimensional phenotyping
Experience in protein design or protein engineering, protein biochemistry or structural biology, or integrating machine learning/protein language models into design or analysis workflows
A track record of open, collaborative work (e.g., preprints, open data, code sharing)
Experience in fast-paced, iterative start-up environments
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