Department / Area
Position Description The Digital, Data, and Design Institute at Harvard is accepting applications for multiple postdoctoral fellows for academic year 2024-2025 to work on research activities at our research labs.
D 3 conducts research at the intersection of academia and practice. For more information on D 3, please visit .The Postdoctoral Fellows will work under the direct supervision of faculty Principal Investigators and the Senior Director of Labs.
They will work closely with the lab manager and research associate at each lab. D 3 is looking for candidates with diverse backgrounds and / or new perspectives.
There are no teaching requirements for these open positions.
The Trustworthy AI Lab, led by HBS Professors Hima Lakkaraju, Marco Iansiti, and Seth Neel and Harvard SEAS Professor Salil Vadhan, is seeking a Postdoctoral Fellow.
The lab focuses on developing algorithms that allow data science practitioners to trade-off ethical considerations like privacy, interpretability, and bias with accuracy, and to mitigate the risks of overfitting.
Recent works on fairness have included new definitions of statistical fairness that account for a more complex protected group structure or a more flexible notion of similarity, new algorithms for efficiently deleting user data from neural networks, the SOTA bounds for adaptive data analysis, and new techniques for differentially private optimization.
Ensuring privacy and fairness in large-scale genomic analyses is a new research interest. Theory of Differential Privacy.
The selected candidate will be expected to lead research in privacy-preserving data analysis / machine learning that is motivated by practice but has a strong theoretical underpinning.
A background and strong interest in differential privacy required. Potential projects could concern private linear regression and related problems, the connection between differential privacy and properties like generalization and replicability, and various relaxations or alternative privacy notions.
Successful applicants will be strong technically as well as have an inclination towards real-world problems. We are looking for applicants with demonstrably strong research skills, ideally, with publications in top venues in machine learning or theoretical CS although this is not a hard requirement . Basic Qualifications
A Ph.D. or equivalent degree in computer science, statistics, or a closely related field.If you have obtained your Ph.
D. in the past 12 months you must be able to provide a certificate of completion from the degree-granting institution OR a letter from the institute’s registrar stating all requirements for the degree have been successfully completed and should verify the date the degree has been conferred. No exceptions.
Additional Qualifications
- Experience implementing DP algorithms and machine learning models in Python preferred.
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