33 cloud-computing-phd-student Postdoctoral positions at Virginia Tech in United-States
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and optimization of measurement-based quantum computing protocols for quantum simulation of quantum many-body models. Preference will be given to candidates familiar with the stabilizer formalism and
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Qualifications - Ph.D. in a biological science such as cell biology, immunology, cancer biology, biochemistry, or related field. PhD must be awarded no more than four years prior to the effective date
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include in vitro neural differentiation, gene expression manipulation, metabolic assays, and mouse breeding and behavior. Knowledge in basic computer skills, record keeping and experience with data
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publications. Additionally, the candidate will contribute to mentoring research technicians and students involved in the project. We are committed to supporting your career development by building on your
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Qualifications - PhD in neuroscience, computer science, or related field. PhD must be awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility remaining
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on their research and innovation campus. Required Qualifications - PhD and/or MD in Computational Biology, Bioinformatics, Genomics, Biology, Data Science, Computer science or other related fields. PhD must be
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opportunities. Required Qualifications • Ph.D. in neuroscience or related discipline. PhD must be awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility
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proposals and stay current with relevant literature. • Mentoring: Mentor undergraduate students and other early-stage trainees alongside the PI. Required Qualifications • PhD in biology, neuroscience, bio
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. Review of applications will begin on July 14, 2025, and continue until the position is filled. Applicants must have completed their PhD by the starting date of the position. Required Qualifications PhD in
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critical role in advancing computational materials science by developing and applying first-principles and machine learning methods, with a focus on interatomic potential development and large-scale