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, biomedicine, and other areas of societal importance. Coding and/or machine learning experiences are highly valued. Specific projects may involve developing multiscale simulation methods for quantum mechanical
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gravitational effects on entangled photons for shining light onto the interface of quantum physics and gravity? Can we exploit quantum photonics technology for novel quantum machine learning, quantum computing
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insurance, retirement plans, and paid time off. To access this tool and learn more about the total value of your benefits, please click on the following link: https://resources.uta.edu/hr/services/records
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field Computer Skills General office suite and willingness to learn lab specific programs Strong programming skills in R and/or Python Experience with Next Generation sequencing Record of peer-reviewed
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desire to learn ex vivo electrophysiology. Position Sponsorship Eligibility: Not eligible for work visa sponsorship About Department/College/Area/ Campus: https://vetmed.wsu.edu/our-team/wsu-profile
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research on how engineers learn, how engineering knowledge and identities are formed, how we assess and evaluate learning, and how educational systems can be designed and transformed to support meaningful
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Description The eBRAIN Lab (https://ebrain4everyone.com ) in the Division of Engineering at New York University Abu Dhabi invites applications for a Post-Doctoral Associate position, to work in the
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candidates whose expertise falls within one or more of the following areas: computational and mathematical modeling, statistical modeling, machine learning, network science, bioinformatics, applied mathematics
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Week: 28 Closing Date : 07-Aug-2026, 6:59:00 PM Disclosure and Barring Service Requirement: Please note that the successful applicant will require DBS disclosure. Further info: https://bit.ly/3DP5K8y
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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