Project Manager II- ML4H

The Machine Learning for Health (ML4H) team at the Broad Institute develops and translates artificial intelligence and machine learning methods to address important problems in human health. ML4H brings together machine learning researchers and engineers clinicians computational scientists and collaborators across the Broad Institute MIT Mass General Brigham and other academic clinical government nonprofit and industry partners. Our work spans large-scale longitudinal electronic health records medical imaging physiological signals and waveforms wearable data genomics clinical text and multimodal biomedical datasets. We develop new AI/ML methods build reusable computational
platforms and datasets evaluate models in real-world clinical settings and work with clinical collaborators toward translation and deployment.

ML4H is seeking an experienced Project Manager to help lead and coordinate this growing portfolio of interdisciplinary research and translational programs. This person will work closely with ML4H leadership and serve as a central operational and strategic partner across the team.

The ideal candidate combines excellent program and project management skills with enough scientific and technical fluency to work effectively with machine learning researchers engineers clinicians computational biologists and external collaborators. They will help turn ambitious scientific goals into well-defined programs coordinate execution across multiple institutions and disciplines identify risks and dependencies and ensure that projects move from ideas to measurable outcomes. The Project Manager will also play an important role in expanding ML4H's collaborative network helping leadership develop new scientific and clinical partnerships and move promising opportunities from initial conversations to active collaborations.

Key Responsibilities

Program Portfolio and Cross-Functional Coordination

• Manage a portfolio of ML4H research engineering infrastructure and translational projects.
• Serve as a key point of coordination among machine learning scientists software and data engineers clinicians computational researchers trainees and program leadership.
• Drive follow-through on decisions and action items while maintaining strong relationships among collaborators with different scientific and organizational priorities.
• Support projects throughout their lifecycle from initial scientific concept and data access through model development evaluation publication validation and potential clinical translation.
• Coordinate activities involving large-scale clinical and biomedical datasets including data access data-use agreements governance and dependencies related to research compliance.
• Identify potential bottlenecks and risks early and work with scientific and technical leads to develop mitigation plans.

Grants and Sponsored Research

• Partner with ML4H leadership investigators research administration and collaborators on the development and execution of externally funded research programs.
• Coordinate complex multi-investigator and multi-institutional grant submissions including timelines contributor responsibilities supporting materials and internal deadlines.
• Support preparation of progress reports scientific updates presentations and other materials for funders and collaborators.
• Maintain a high-level view of the ML4H funding portfolio including active projects upcoming renewals new opportunities and major proposal deadlines.
• Help ensure alignment between funded commitments scientific priorities staffing and available resources.

Collaboration Development and Strategic Engagement

• Coordinate and participate in meetings with prospective collaborators to understand their scientific and clinical interests identify areas of alignment with ML4H capabilities and define potential joint projects.
• Prepare leadership for external meetings by developing agendas background materials summaries of relevant ML4H work and potential areas for collaboration.
• Drive follow-up after exploratory meetings including documenting opportunities connecting relevant investigators and team members defining next steps and tracking potential collaborations through to project initiation.
• Help organize and support ML4H scientific and community-building activities including the ML4H Seminar Series workshops brainstorming sessions and targeted meetings that bring together ML4H researchers with clinicians scientists and external partners around new research opportunities.
• Help maintain visibility into publications software releases datasets models grants collaborations presentations reports and other outputs across the program.
• Support onboarding of new collaborators and team members into ML4H projects and processes.

Qualifications
Required

• Bachelors degree with at least 8 years of relevant professional experience in project or program management scientific research biotechnology healthcare technology or a related environment.
• Demonstrated experience managing complex projects involving multiple teams stakeholders and dependencies with strong organizational skills and attention to detail.
• Excellent written and verbal communication skills with the ability to communicate effectively with scientists engineers clinicians administrators and senior leadership.
• Strong judgment and ability to identify priorities anticipate problems and drive projects toward resolution.
• Ability to work independently establish structure in ambiguous or evolving situations and take ownership of projects from planning through execution.
• Strong interpersonal skills and demonstrated ability to build trusted relationships across disciplines and organizations.

Preferred

• Advanced degree with at least 6 years of relevant professional experience in a scientific or technical field such as computer science machine learning biomedical informatics computational biology engineering public health or a related discipline.
• Experience managing AI/ML computational research data science biomedical research or software engineering programs with familiarity with machine learning concepts and the ML research lifecycle.
• Experience working with clinical or biomedical data and an understanding of issues related to data access privacy governance and research compliance.
• Experience working in academic medicine biomedical research biotechnology or a similar research intensive environment.
• Experience coordinating NIH or other federal grants and multi-investigator research programs.
• Experience managing collaborations across multiple institutions.
• Familiarity with software development cloud computing data platforms or research computing environments.
• Experience supporting scientific publications conferences workshops or research community building activities.

What Success Looks Like
The Project Manager will become a trusted partner to ML4H leadership and the broader team. Within the first year this person will have developed a strong understanding of ML4Hs scientific portfolio and collaborators and established effective systems for managing projects across the program.
Success in this role means that:

• ML4H leadership has clear visibility into the status priorities risks and resource needs of major projects.
• Scientific and technical teams spend less time resolving operational and coordination issues and more time advancing the science.
• Complex collaborations have clear ownership timelines decisions and next steps.
• Grant commitments project milestones and external deliverables are proactively managed.
• Potential delays and dependencies are identified before they become major problems.
• New projects move efficiently from ideas into well-structured programs.
• Promising external conversations are systematically followed through and when appropriate converted into active collaborations proposals data opportunities or projects.
• ML4H can scale its research portfolio and collaborations without losing the flexibility and scientific creativity that are central to the team.

The Broad will not provide sponsorship for this role.