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

• Bachelor's 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 ML4H's 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.

The expected base pay range for this position as listed above is based on a 40 hour per week schedule. Broad provides pay ranges representing its reasonable and good faith estimate of what the organization reasonably expects to pay for a position at the time of posting. Actual compensation will vary based on factors including but not limited to, relevant skills, experience, education, qualifications, and other factors permissible by law.

At Broad, your base pay is just one part of a comprehensive total rewards package. From day one, this role offers a competitive benefits package including medical, dental, vision, life, and disability insurance; a 401(k) retirement plan; flexible spending and health savings accounts; at least 13 paid holidays; winter closure; paid time off; parental and family care leave; and an employee assistance program, among other Broad benefits.

The Broad Institute is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, disability, protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.

Should you need a reasonable accommodation to complete the application or interview process, please contact [email protected] for assistance.