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collection, management, and analysis. Program experiments. Create stimuli by collecting and designing “myths and facts”. Other duties and projects as requested such as assist with human subjects’ applications
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experience in any of the following: molecular biology (particularly gene design and expression and protein purification), single-channel measurements, data analysis (python programming and use preferred
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of mass timber structures to the design and testing of a novel Deconstructable CLT and steel composite floor system. Conduct in-depth analysis of acoustics and vibrations of a CLT and steel composite floor
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the names of at least two mentors/supervisors or senior colleagues who will be able to provide (upon request) letters of recommendation. About The Roux Institute The Roux Institute is designed as an engine
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the names of at least two mentors/supervisors or senior colleagues who will be able to provide (upon request) letters of recommendation. About The Roux Institute The Roux Institute is designed as an engine
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, the researcher will assist with the development of machine learning algorithms for design synthesis. Position Type Temporary Additional Information Northeastern University considers factors such as candidate work
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at conferences and in research publications, as well as grant writing. Successful candidates should have strong technical skills, including experiment design and data analysis, along with excellent management and
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intereactions in the broad field of glycoprotein-based therapeutic design. Strong background and experience with applications of machine learning (especially Explainable Artificial Intelligence – XAI) is required
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on passive RF tags and antenna design. Qualifications: A Ph.D. in Electrical Engineering or a closely related field. Demonstrated expertise in circuit design and electromagnetic modeling is essential
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About the Opportunity Outstanding candidates are sought for an experimental postdoctoral opportunity on Northeastern’s Boston Campus to assist in the design and validation of computationally derived