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or development of machine learning methods, or a desire to learn these skills, are also welcome. We offer the opportunity to work on interesting scientific challenges using modern experimental methods available in
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learning, offers powerful solutions to automate these tasks and provide reliable real-time information. This doctoral project is part of a 5-year research chair on Computer vision applied to the swine sector
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that demand interdisciplinary solutions? Then the Program for Collaborative Doctoral Projects is the perfect opportunity for you. Many of today’s most pressing problems can only be tackled through
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(NREL), where world-class scientists, engineers, and experts are accelerating energy innovation through breakthrough research and systems integration. From our mission to our collaborative culture, NREL
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for medical imaging, tailored for deep learning. The high-level goal of the project is simple: to use anatomical knowledge and existing knowledge as training data for deep neural networks (instead of manual
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learning tools to recommend reaction conditions for the synthesis of novel TRPA1 inhibitors. The project “A machine learning approach to computer assisted drug design” is led by Docent Juri Timonen
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the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity
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Section, Department of Civil and Mechanical Engineering, Technical University of Denmark (DTU). We look for a talented, self-driven, and collaborative individual with a passion for tackling complex
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collaborative efforts among researchers at the University of Utah and UC San Diego in developing and applying methods in predictive and causal modeling of complex biomedical and social processes and systems
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public datasets as well as samples generated through collaborations. Ideal candidates will have strong interests in microbiome-host biology, bioinformatics, or machine learning. Experience with R or Python