QualificationsResearchNumPySciPyData center experienceMATLABDoctoral degreeMaster of ScienceMaster’s degreeDoctor of Philosophy
Research Scientist, Physical Modeling Responsibilities:
Lead and collaborate on projects with a globally based team of researchers and engineers inside and outside of Meta.
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 Meta.
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.
Minimum Qualifications:
PhD (or M.S. + equivalent experience) in Physics, Engineering or a related technical field
8+ years of hands-on experience developing physics based models and simulations
3+ years of technical leadership experience architecting, developing, and launching hardware/software projects and/or services
Knowledge and experience of scientific coding and numerical computation methods using Python (NumPy/SciPy), Julia, MATLAB, etc.
Experience in quantitative measurements of noisy data, through a demonstrated track record in experimental physics, engineering, data science or a similar discipline
Demonstrated track record of starting and leading interdisciplinary research and engineering projects
Experience communicating technical projects to both technical and non-technical audiences
Experience working on cross-functional teams and matrixed organizations
Preferred Qualifications:
Experience working on a wide range of technologies spanning multiple disciplines in particular physics and data science and machine learning
Experience in the thermal and power modeling, data center and sustainability space
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