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do: Design, fabricate, characterize, and optimize electrochemical biosensing technologies for real-time detection. Develop and implement novel surface chemistries to improve sensor performance
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publications representative of your work and research interests, ideally related to Riemannian Optimization. Contact Information Melanie Weber Contact Email mweber@seas.harvard.edu Salary Range $67,600 – $91,826
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. Candidates will perform research on agentic AI, foundational modeling, optimization, and control of multiagent autonomous systems with an application in renewable energy and power grids, in addition to working
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fellow with a Ph.D. in electrical engineering, applied mathematics, or related field. Candidates will perform research on agentic AI, foundational modeling, optimization, and control of multiagent
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publications representative of your work and research interests, ideally related to Riemannian Optimization. Contact Information Melanie Weber Contact Email mweber@seas.harvard.edu Salary Range Minimum Number
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: 15586 School: Harvard Business School Position Description: The Digital Data Design (D^3) Institute and the LISH/Data Science & AI Operations Lab seek enthusiastic Postdoctoral Fellows skilled in
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, and optimization to address challenges created by the operationalization of AI within partner organizations. The Postdoctoral Fellows will play a pivotal role within the LISH/Data and Science Operation
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models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees. Research areas include Representation Learning, Machine learning and Optimization
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Together, these research directions seek to reimagine how buildings and cities operate—optimizing energy use, enhancing human well-being, and reducing carbon emissions at scale. We are seeking multiple
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team. Learn more about the innovative work led by Dr. Don Ingber here: https://wyss.harvard.edu/technology/human-organs-on-chips/ . What you’ll do: Design, fabricate, characterize, and optimize