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Bill and Melinda Gates Foundation Research Scientist | Institute for Disease Modeling, Malaria in Seattle, Washington

The Foundation

We are the largest nonprofit fighting poverty, disease, and inequity around the world. Founded on a simple premise: people everywhere, regardless of identity or circumstances, should have the chance to live healthy, productive lives. We believe our employees should reflect the rich diversity of the global populations we aim to serve. We provide an exceptional benefits package to employees and their families which include comprehensive medical, dental, and vision coverage with no premiums, generous paid time off, paid family leave, foundation-paid retirement contribution, regional holidays, and opportunities to engage in several employee communities. As a workplace, we’re committed to creating an environment for you to thrive both personally and professionally.

The Team

The Institute for Disease Modeling (IDM) is an embedded research institute within the Bill and Melinda Gates Foundation’s Global Health Division that uses computational modeling and data analysis to support policymakers in global health. Staff at IDM work with a wide ecosystem of partners including universities, NGOs, government ministries, other research organizations, and public health institutions. Through our research, IDM shapes global efforts to eradicate infectious disease and to achieve permanent improvements in the health of those most in need.

Application deadline: Friday, October 11 (11:59 PM PDT)

Your Role

As a member of the IDM Malaria Team, the Research Scientist will generate quantitative evidence to inform decisions that reduce malaria burden and accelerate eradication. Our portfolio spans a broad range of topics, with projects that touch on epidemiological research, product evaluation, operational support, and global strategy. Through rigorous and creative use of models and analytics, members of the team collaborate to :

  • Realistically assess the current burden of disease in diverse settings.

  • Understand the strengths and weaknesses of existing strategies to combat malaria.

  • Prospectively explore how nascent technologies and novel concepts could be leveraged in the fight against malaria in the future.

  • Develop new methodological approaches for tackling the above.

  • Engage with stakeholders at all levels from students to global policymakers to support the malaria analytic ecosystem.

    What You ’ll Do

  • Collaborate on the development, refinement, and application of malaria transmission models. Think deeply about what models can and can’t do, how our models can be improved, and how technical limitations might impact real-world decisions that are taken using your analysis.

  • Imaginatively apply both traditional and bespoke analytics to understand complex, noisy, or incomplete data.

  • Grow and support a network of collaborators inside and outside the Gates Foundation, spanning the realms of research, academia, policy, implementation, and funding; exercise clear communication across audiences with diverse areas of expertise.

  • Work closely with partners to pinpoint critical questions that can be supported by modeling and translate those needs to analysis.

  • Create poignant visualizations to tell the stories that underlie your results.

  • Learn from partners and take the initiative to p erpetually grow your knowledge of malaria epidemiology, operations, and policy , for contextual understanding of the questions we aim to address.

    Your Experience

  • Ph.D. in epidemiology, mathematics, engineering, computational biology, or a related quantitative field preferred. Master's degree required.

  • Experience using computational modeling and data analysis to solve scientific problems; practical literacy in the concepts of model cal ibration, model validation, sensitivity analysis, and model uncertainty strongly desired; previous work with cleaning, plotting and interpreting noisy data would be highly beneficial.

  • A love of visualizing data and modeling results in telling a scientific story , and the ability to adapt your narrative to different audiences.

  • Proficiency in at least one data-analysis or scripting language (python and R preferred); familiarity with C/C++ helpful .

  • Knowledge of and passion for public health issues in LMIC settings . Prior research in malaria is an asset but is not required .

  • Application deadline: Friday, October 11 (11:59 PM PDT)

  • The salary range for this role is $ 166,3 00 to $ 249 , 5 00 USD.  We recognize high-wage market differences in Seattle and Washington D.C. where our offices are located .  The range for this role in these locations is $ 181 , 2 00 to $ 271 , 8 00 USD.  As a mission-driven organization, we strive to balance competitive pay with our mission and new hires are typically brought into the organization at a salary between the range minimum and the salary range midpoint. Actual placement in the range will depend on a candidate’s job-related skills, experience, and expertise , as evaluated during the interview process.

  • Must be able to legally work in the country where this position is located without visa sponsorship.

Hiring Requirements

As part of our standard hiring process for new employees, employment will be contingent upon successful completion of a background check.

Candidate Accommodations

If you require assistance due to a disability in the application or recruitment process, please submit a request here.

Inclusion Statement

We are dedicated to the belief that all lives have equal value. We strive for a global and cultural workplace that supports ever greater diversity, equity, and inclusion — of voices, ideas, and approaches — and we support this diversity through all our employment practices.

All applicants and employees who are drawn to serve our mission will enjoy equality of opportunity and fair treatment without regard to race, color, age, religion, pregnancy, sex, sexual orientation, disability, gender identity, gender expression, national origin, genetic information, veteran status, marital status, and prior protected activity.

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