Research Scientist - Physical Modeling
- Menlo Park, CA
Facebook's mission is to give people the power to build community and bring the world closer together. Through our family of apps and services, we're building a different kind of company that connects billions of people around the world, gives them ways to share what matters most to them, and helps bring people closer together. Whether we're creating new products or helping a small business expand its reach, people at Facebook are builders at heart. Our global teams are constantly iterating, solving problems, and working together to empower people around the world to build community and connect in meaningful ways. Together, we can help people build stronger communities - we're just getting started.
We are looking for someone adept at collaboratively identifying and evaluating opportunities from a global level to the nanoscale, in a variety of domains that include, but are not limited to physics, numerical and analytical modeling, data science, machine learning, experimental physics/EE and interdisciplinary projects. We're also looking for someone who demonstrated success as a research or technical lead.
- Lead and collaborate on projects with a globally based team of researchers and engineers inside and outside of Facebook.
- Translate ambiguous ideas into well-defined projects and de-risk technical and execution challenges.
- Lead projects from inception into a phase of deployment and scaling.
- Work on interdisciplinary projects and teams and identify and explore interdisciplinary opportunities, in particular bridging between the physical sciences and data science and machine learning addressing challenges directly relevant to Facebook.
- Work with cross-functional teams to establish support, collaborations and end users of the developed methodologies, tools and datasets.
- Foster a positive, creative and collaborative environment, encouraging an openness to support and try out new and unconventional ideas.
- Share results internally and externally through means of publications, presentations and blog posts.
- B.S. or M.S. in Physics, Electrical Engineering or a related technical field
- 5+ years of technical leadership experience architecting, developing, and launching hardware/software projects and/or services
- Experience in quantitative measurements of noisy data, through e.g. demonstrated track record in experimental physics, high energy physics, data science or a similar discipline
- Demonstrated track record of starting and leading interdisciplinary research and engineering projects
- Experience communicating projects to both technical and non-technical audiences
- Experience working on cross-functional teams and matrixed organizations
- Experience working on a wide range of technologies spanning multiple disciplines in particular physics and data science and machine learning
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