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inverse modeling methods, machine learning, and artificial intelligence techniques. Appointment Details: Start date: As early as February 1, 2026. Annual Salary: $52,000 Application review: Ongoing until
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Computational complexity in adiabatic quantum computation AI to boost quantum technologies (e.g., machine learning for quantum error prevention/mitigation/correction) Quantum machine learning Quantum cloud
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in live or fixed organisms, cells or tissues - Experience with data analysis in Python, R or similar - Experience working with animal models AND - Experience with mass spectrometry, including sample
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, database management, and fulfilling sample requests. In addition, the candidate will work with the research team to plan and perform experiments utilizing complex procedures and techniques, troubleshoot
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amyotrophic lateral sclerosis (ALS). Projects will involve gut microbiota manipulation and in vivo multiphoton imaging of the brain using animal models of ALS. The desired candidate will have experience in
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University of British Columbia | Northern British Columbia Fort Nelson, British Columbia | Canada | 3 months ago
knowledge to resolve or aid in the resolution of complex scientific and technical problems with students. Qualifications PhD in Physics, Electrical Engineering, or a related discipline. Demonstrable skill in
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have expertise in working with animal disease models, single-cell and spatial RNA sequencing technology, and a solid understanding of the CNS immune landscape. Additionally, applicants should have at
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Grant (ORF-RE (external link) ). The SSHRC-funded project was launched in 2021 and the objectives of this research are to: 1) expand conceptual models for intergenerational partnerships; 2) investigate
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Grant (ORF-RE (external link) ). The SSHRC-funded project was launched in 2021 and the objectives of this research are to: 1) expand conceptual models for intergenerational partnerships; 2) investigate
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, imaging techniques, and modeling of complex systems have created opportunities for exciting research careers at the interface between the physical/ computational sciences and the biological