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Background in machine learning or deep learning methods, including Graph Neural Network (GNN) Experience with Large Language Models (LLMs) applied to biological data collection, extraction, and standardization
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EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description ELLIS Institute Finland is a newly established world-class research hub in AI and machine
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1. A PhD degree in a relevant area, e.g., Chemical Engineering, Control Engineering, Computer Science, Systems Engineering, etc. 2. The candidates should have strong math, modeling, programming, and scientific writing skills, and prior experience in at least one of the following areas: a....
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Posting Details Position Information Posting Number SF02201 Job Title Computer Systems Administrator Position Number 107036 FTE 1.00 FLSA Exempt Position Type Professional Staff Union PSA/NEA
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Posting Details Position Information Posting Number SF02221 Job Title Computer Systems Administrator Position Number 107036 FTE 1.00 FLSA Exempt Position Type Professional Staff Union PTAA
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Lawrence Berkeley National Laboratory is hiring a Postdoctoral Researcher – Machine Learning for Materials Science within the Molecular Foundry division. Molecular Foundry is a Department of Energy
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project entitled "Energy Storage as an Enabler of Sustainability through Optimization, Machine Learning, and High-Performance Computing," supported by the Dieter Schwarz Foundation through a Courageous
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nearby state and national parks. Job Description: The Department of Electrical and Computer Engineering (ECE) at The University of Texas at El Paso (UTEP) invites applications for a tenure-track Assistant
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of Vacancy Number ST2600180 Job Title Computer Technician II Job Category Regular Student Job Job Type Regular Student Jobs Position Class Code 82100 Student Employee Student Pay Grade 999 Hourly Wage/Salary
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Job description We invite applications for a fully funded PhD position in the area of Scientific Machine Learning (SciML), which integrates data-driven machine learning techniques with established