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on healthcare, research, and teaching, we bear a unique responsibility – ideally with you on board! The position is based at the Institute of Medical Informatics within the research group Machine Learning
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Requisition Id 15751 Overview: The Advanced Computing in Health Sciences (ACH) section at the Oak Ridge National Laboratory is seeking qualified applicants for a Machine Learning Engineer position
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machine learning. We focus on inductive logic programming (ILP), which learns logical rules from data. We primarily use automated reasoning techniques, such as SAT/ASP/SMT/MaxSAT solvers, to learn rules
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Research Scientific Computing Center (NERSC ) at Berkeley Lab seeks a highly motivated Postdoctoral Researcher -- Scientific Machine Learning (NESAP) to join the Workflow Readiness team as part of NERSC's
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and machine learning. We focus on inductive logic programming (ILP), a form of inductive program synthesis which learns logical rules from data. The focus of this position is to develop ILP/program
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part-time positions are available for those committed to application-oriented education. Job Responsibilities Teach and assess at least 3 courses in the following core subjects: Data Analytics & Machine
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Center for Devices and Radiological Health (CDRH) | Southern Md Facility, Maryland | United States | about 4 hours ago
image processing, disease detection, diagnosis, and therapeutic monitoring. The program addresses critical regulatory challenges posed by AI devices that can continuously learn and adapt, including
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expected to contribute to the development and application of advanced manufacturing simulations, and machine learning (ML) models relevant to additive manufacturing, virtual manufacturing, material
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-on experience in autonomous robotics projects; exposure to deep learning or reinforcement learning is a plus. Strong problem-solving ability, collaborative and independent work style, willingness to learn new
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candidate will: Develop genome-scale metabolic models (GEMs) for engineered microbial strains. Design and implement machine learning algorithms to predict strain performance and optimise metabolic pathways