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/Scientist IV, Electrical and Computer Engineering Posting Number req25245 Department Electrical and Computer Engr Department Website Link https://ece.engineering.arizona.edu/ Location Tucson Campus Address
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with experience in ligand discovery. Our research group is focused on developing state-of-the-art computational methods for ligand/drug discovery, using machine learning, high-performance/cloud computing
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program, an artist in residence program, and a summer program. Reporting to the Institute Manager, the Event Coordinator will plan, organize, coordinate and facilitate assigned events. Responsible for a
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discovery. Preference will be given to candidates with expertise in AI and ML methodologies complemented with experience in the utilization of advanced computing technologies such as HPC and/or cloud
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implement cloud-native data pipelines connecting lab instruments, databases, and AI models Support model deployment, inference services, and experiment tracking (e.g., MLflow) Integrate LLM reasoning with
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Researcher (R2) Positions Postdoc Positions Application Deadline 9 Mar 2026 - 23:59 (Europe/Zagreb) Country Croatia Type of Contract Temporary Job Status Full-time Hours Per Week 40 Offer Starting Date 6 Feb
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diseases. Additional details about the lab can be found at http://ismagilovlab.caltech.edu/ Essential Job Duties Assist graduate students, postdocs, and research staff with bioinformatics/computational
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
Experience with version control systems such as GitHub, cloud- or cluster-based computing, systems management, statistical programming or mechanistic modeling, interactive data visualization (e.g., dashboards
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Cryptography that conducts research into mobile device, cloud, and platform security. Our Education. SCIS has more than 100 students enrolled in the Ph.D. in Information Systems and Ph.D. in Computer
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, https://hal.science/hal-04930868 . [2] Peyré, G., Cuturi, M., et al. (2019). Computational optimal transport: With applications to data science. Foundations and Trends in Machine Learning, 11(5-6):355–607