1,077 high-performance-quantum-computing-"https:"-"https:" Postdoctoral positions in United States
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Python and either PyTorch or TensorFlow is required Experience using High-Performance Computers (HPCs) is preferred Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork
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Postdoctoral Research Associate - Hybrid Computational-Experimental Scientist in Bacterial Drug Resp
Job Description We are seeking an interdisciplinary postdoctoral researcher to join our lab at St. Jude Children's Research Hospital to develop new experimental-computational approaches for studying
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: 2024120 Carnegie Mellon University is a private, global research university that stands among the world's most renowned education institutions. With ground-breaking brain science, path-breaking performances
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Harvard Brain Science Initiative: HBI Postdoctoral Pioneers Program Deadline Month: October (LOI) and November (full application) Description: Harvard Brain Science Initiative (HBI) aims to support
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Carnegie Mellon University is a private, global research university that stands among the world’s most renowned education institutions. With ground-breaking brain science, path-breaking performances
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performs scientific research and studies under the supervision of managing staff. Moreover, the Postdoctoral Associate promotes institutional recognition through literal contributions to the scientific
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Job Description Apply now Req Id: 30365 Job Title: Post Doc Research Associate Department of Physics & Astronomy City: West Lafayette Job Description: Job Summary Quantum Device Fabrication
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to apply for a faculty or staff position, please review this tip sheet . The Department of Informatics and Health Data Science has an exciting opportunity for a full-time Postdoctoral Scholar to work on the
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program in the realm of quantum mathematics and to interact with the other faculty and students in the group. Preference will be given to candidates who have a track record of high-quality research in
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. The candidate will lead computational analyses of these datasets, using the laboratory’s suite of existing AI/ML tools to assign structures to unidentified peaks in metabolomic datasets (e.g., https