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Requisition Id 16722 Overview: We are seeking a Postdoctoral Research Associate within the Advanced Machining and Machine Tool Research Group who will focus on developing, evaluating, and
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 12 hours ago
Job Requirements REQUIRED: PhD in a field of quantitative science; strong background in machine learning and signal processing; experience with and commitment to rigorous and reproducible
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increasingly autonomous and agentic models. The research will examine frontier AI systems that interact with operating systems, APIs, software tools, other agents, and complex environments, moving beyond text
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 12 hours ago
performance utilizing a variety of tools including life-cycle assessment (LCA), machine learning techniques, and/or optimization methods. This position will carry out state of the art research into the economic
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particular focus on increasingly autonomous and agentic models. The research will examine frontier AI systems that interact with operating systems, APIs, software tools, other agents, and complex environments
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, the successful candidate will lead the development of a software tool to infer more realistic scenarios of speciation from genomic data. The Postdoctoral Research Scholar will also have the opportunity
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Experience developing software with Python, R, and/or Julia Experience with machine learning and AI algorithms and tooling (e.g. PyTorch) Experience with remote sensing and open-source GIS tools (e.g. Google
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, GIS tools and quantitative/spatial approaches including machine learning to understand how wildlife species are reacting to climate change at continental or global scales. Specific project ideas could
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imaging, digital pathology, and spatial omics datasets for research projects. - Support computational image analysis, data annotation, and quality assurance activities using established software tools and
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or applying machine learning models. Proficiency in programming and data analysis using Python, R, or comparable analytical tools. Demonstrated ability in scientific writing, peer-reviewed publication, and