11 algorithm-development-"the"-"The-Netherlands-Cancer-Institute" PhD positions in United States
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preprocessing IoMT network traffic datasets. Implement and evaluate machine learning algorithms (e.g., logistic regression, SVM, random forest) for intrusion detection. Develop prototype software tools (e.g
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. Responsibility: * Develop or integrate novel statistical methods and algorithms for analyzing large-scale -omics data, including gene regulatory network inference, cell lineage reconstruction, multi-dimensional
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join a growing, interdisciplinary team whose projects span laboratory-level and nationally significant DOE missions. Essential Duties and Responsibilities Develop novel machine learning algorithms and
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performance. Duties and responsibilities include the development of new abstractions and algorithms using computational sheaf theory. Such algorithms will be developed for understanding composite energy-driven
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modelling. Experience in developing and using innovative tools and methods, algorithms, computer programming, and GNSS/Satellite data. Knowledge of programming language, including experience in developing
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and Saeys teams. In this research project you will develop and apply algorithms to link clinical phenotypes of metastasis to molecular phenotypes in mouse models. It is known that metastases exhibit
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deep learning and scalable deployment Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches Design and run experiments using the latest
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(NREL), located at the foothills of the Rocky Mountains in Golden, Colorado is the nation's primary laboratory for energy systems research and development. Join the National Renewable Energy Laboratory
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scalable deployment Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches Design and run experiments using the latest ML tools and frameworks
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hierarchies during cardiac, endothelial and hematopoietic development. Responsibility: * Develop or integrate novel statistical methods and algorithms for analyzing large-scale -omics data, including gene