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the research activities of Pratt Institute under one roof in the Brooklyn Navy Yard (BNY). Since our founding in 1887, Pratt has upheld the belief that education should be accessible to all who wish to learn. As
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to oversee research activities outlined in NSF Grant 2520154 “Understanding Expectation-Driven Learning in Early Childhood: An Experimental and Computational Investigation,” under the supervision of Dr. Kimele
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
, or other novel/emerging pollutants - Developing / implementing advance machine learning algorithms for environmental datasets - Attention to detail and careful documentation of work products such as How
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predictive modelling; Bioinformatics and Knowledge Graphs (visualization and reporting); AI-based data integration across cohorts (with federated machine learning); Contribute to ongoing projects, such as: o
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programs and ability to learn new ones. Commitment to inclusive excellence. Pay Range Minimum $27.30, Midpoint $32.50, Maximum $37.70 Salary is based on related experience, expertise, and internal equity
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familiar with data science and machine/deep learning toolkits. Experience with model deployment and the usage of MLOps tools (Dockerization, CI/CD pipelines, edge infrastructure, etc.) is a plus. As a PhD
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applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in process industries; advanced process control (APC); model predictive control (MPC); digital
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engineering service offerings. Other necessary skills: MLOps Experience: Demonstrated experience in operationalizing and maintaining machine learning models in production environments, including deployment
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. Proficiency in programming languages for data analysis (e.g., Python, R) and experience with machine learning, statistical modeling, and wearable sensor data analysis is desirable. We expect you to be able
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program (2025.02832.MAD), funded by FCT-Madeira, under the following conditions: I. Scientific Area: Electrical Engineering and Computer Engineering II. Admission Requirements