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computing applications—mainly for a SWaP-constrained AV—using hybrid electro-photonic accelerators. We propose to design and prototype a complete electro-photonic computing (EPiC) system (CPUs + accelerators
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Institute for Climate and Sustainability. While the project is scheduled to launch in September, hiring may occur earlier, and selected candidates may have the opportunity to begin their appointments ahead
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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● Familiarity with single cell data analysis is preferred, but not required. ● Experience using a shared computing environment and a scheduler such as SLURM or qsub preferred ● Experience designing
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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systems or systematics. Combining operators You can combine the operators above to fine-tune your results: +"artificial intelligence" algorithm +robot -machine → Shows results only if they include
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preferred, and this can take various forms: working with large model simulations or large data, compiled programming languages, algorithms, etc. The position is an especially good match for candidates
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schedule with regular evening hours, occasional weekends, and some travel. Learn more about our work culture and see yourself at Harvard Kennedy School. We regret that the Harvard Kennedy School does not
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. This role is offered as a hybrid (some combination of onsite and remote) where you are required to be onsite at our Boston, MA based campus. Specific days and schedule will be determined between you and the
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process Aspiring Fellows should prepare a cover letter and CV or resume. If your application matches our needs, we will reach out to schedule a meeting with a member of the fellowship program to determine