120 postdoc-in-thermal-network-of-the-physical-building Fellowship research jobs in Canada
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are committed to providing an inclusive and barrier-free work environment, starting with the hiring process. If you need to be accommodated during any phase of the evaluation process, please use the Contact
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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | about 21 hours ago
these needs and how we can be of assistance. Dalhousie University is committed to ensuring all candidates have full, fair, and equitable participation in the hiring process. Our complete Accommodation
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are awarded without regard to religion, gender, age or ethnicity. Azrieli International Postdoctoral Fellows join a network of outstanding early-career scientists and scholars. They enjoy opportunities
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advanced degree (PhD) in physics, applied mathematics, chemistry or electrical engineering, and should have a background in experimental quantum systems. Experience with magnetic resonance, Hamiltonian
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this hiring process we are committed to creating an inclusive and equitable process for all candidates (including but not limited to people with disabilities). Confidential accommodations are available
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this hiring process we are committed to creating an inclusive and equitable process for all candidates (including but not limited to people with disabilities). Confidential accommodations are available
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. - Must be registered as a Postdoctoral Fellow with McGill University. Field of Study: Neuroscience, Molecular biology, Physics Required Skills • Excellent French and English, spoken and written
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provide stipendiary support to recent PhD graduates who are: undertaking original research; publishing research findings; developing and expanding personal research networks; broadening their teaching
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. Qualifications: Applicants must have a PhD in mathematics or physics by the start of the fellowship. Application Instructions: Applicants should submit the following materials through MathJobs: Curriculum Vitae
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the last 5 years or soon to be completed. Demonstrated experience in building machine learning/deep learning models using one or more large scientific data sets involving sequence, protein structures