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UNIVERSIDAD CATÓLICA DE MURCIA - FUNDACIÓN UNIVERSITARIA SAN ANTONIO DE MURCIA | Spain | about 1 month ago
. Through advanced Machine Learning and Deep Learning technologies, it seeks to automate agronomic processes, optimize resource use, and maximize production in a sustainable way. Main duties Design
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Deep Learning (CIDL), part of the Leiden Institute of Advanced Computer Science (LIACS). As a team, we develop cutting-edge techniques for advanced computational imaging systems, combining expertise from
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doctoral student in the field of chemistry to work on development of deep learning models for estimating protein-ligand binding energies. The specific project is a part of a large-scale collaboration
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subgroups Support public health policy, prevention and hospital planning Provide meaningful feedback to patients, clinicians and policymakers The PhD will work at the interface of machine learning, deep
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deep learning to support ongoing research projects involving large-scale healthcare and biomedical datasets. The Research Assistant will work closely with faculty on data-driven research, model
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learning algorithms that are focused on human behavior modeling related to video classification using deep learning networks for end-users. Work with other team members to develop and maintain software
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, and interdisciplinary research team, RE will develop and implement deep learning algorithms to analyze trap camera footage for wildlife monitoring and conservation efforts. Job Responsibilities
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Background Check: Yes About the Department: The Department of Psychology (https://psychology.gmu.edu/) boasts over 1,700 undergraduate majors (BS, BA), 330 graduate students (PhD, MA, MPS), and 50 full-time
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information sources and to provide the relevant analysis of all the available variables in different scenarios conditions. In order to reach this goal, deep learning-based algorithms will be implemented
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develop new and creative approaches based on operations research, artificial intelligence, machine/deep learning or similar methodologies, to improve the design and performance of future manufacturing