19 condition-monitoring-machine-learning Postdoctoral positions at Massachusetts Institute of Technology
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neoclassical tearing modes in metal-wall scenarios; support the creation and validation of machine learning (ML) and hybrid physics + ML models to monitor and control the proximity to stability boundaries
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Requirements REQUIRED: Ph.D. in Atmospheric science, Civil and Environmental engineering, mechanical engineering, or a related field; knowledge of and demonstrated skillset in physics-informed machine learning
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supermassive black holes through a combination of observational data, machine learning techniques, and cosmological simulations. The group is actively involved in multiple JWST Guaranteed Time Observation (GTO
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 16 hours ago
, reinforcement learning, theoretical statistics, or related fields. Applicants should have a solid background in probability and statistics/machine learning. The postdoctoral fellow will be mentored by Alexander
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 1 month ago
Posting Description POSTDOCTORAL ASSOCIATE, Mechanical Engineering, to perform cutting-edge research on projects centered around machine learning models for Computer Aided Design and Engineering
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 2 months ago
how circuit structure supports computation. Will lead research on one or more of the following areas: Automated proofreading & annotation at scale: Machine learning approaches for error detection, human
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/supporting applications development and experiment realizations on DIII-D and international tokamaks; support the creation and validation of machine learning models, particularly in areas like plasma
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 1 month ago
/supporting applications development and experiment realizations on DIII-D and international tokamaks; support the creation and validation of machine learning models, particularly in areas like plasma
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Received: The position works closely with Professors Sertac Karaman and Eric So. Position requires ability to perform with minimal supervision. Supervision Exercised: No direct reports. May monitor
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 16 hours ago
at least one public lecture at MIT during the fellowship term; -Teach one course per academic year, determined in consultation with the History faculty and aligned with both the fellow’s expertise and the