Microsoft Corporation Research Intern - Cryptography and Machine Learning and Optimization groups in Redmond, Washington
We are looking for interns to participate in an ongoing collaboration between Cryptography and Machine Learning and Optimization groups on the Machine Learning over Encrypted Datasets.
The goal is to blend secure computation techniques (Fully-Homomorphic Encryption, Secure Multi-Party Computation) with the modern machine learning tools (deep neural networks etc.) in order to advance the field of machine learning over sensitive datasets.
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We expect interns to conduct both theoretical and applied research in the field of privacy-preserving machine learning. This includes: designing new algorithms, building new cryptographic primitives, producing prototype implementations, and evaluating them on real-world datasets.
In addition to the qualifications below, you’ll need submit a minimum of two reference letters for this position. After you submit your application, a request for letters may be sent to your list of references on your behalf. Note that reference letters cannot be requested until after you have submitted your application, and furthermore, that they might not be automatically requested for all candidates. You may wish to alert your letter writers in advance, so they will be ready to submit your letter.
Must be currently enrolled in a PhD program in Computer Science or a related STEM field.
Must have at least 1 year of experience in conducting research and writing peer-reviewed publications.
Expertise in theoretical and applied aspects of Fully-Homomorphic Encryption and Multi-Party Computation
Hands-on experience in applied machine learning
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